1.
TARRo2
Design Brief
April 2016

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TARRo2 DESIGN BRIEF 1
TARRo2 Design Brief
Submitted to: UCI Rescue Robotics Competition
Jonivan Artates
Xochitl Alvarado
Jose Antelo
Joe Wijoyo
Amal Edick
Brian Mauricio
Haowen Wong
Wyeth Binder
Naziha Kibria
Sina Habibizad
ASEC RAG
Professor Jack Appleman
Irvine Valley College
April 2016

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TARRo2 DESIGN BRIEF 2
TABLE OF CONTENTS Pg #
EXECUTIVE SUMMARY ……………………………………….................................. 3
I . CONFIGURATION DESIGN ……………………………………………………….. 4
1: Assessment…………………………………………………………………….... 5
2: First Responder Interface……………………………………………………….. 7
3: Navigation………………………………………………………………………. 8
4: Mobility…………………………………………………………………………. 9
5: Power & Safety…………………………………………………………………. 10
6: Structure……………………………………………………………………….... 11
II. TEAM & FACULTY INFORMATION ……………………………………………. 12
III. PROJECT ORGANIZATION & OUTREACH ……………….…………………. 13
1: Timeline………………………………………………........................................ 13
2: Marketing………………………………………………………………....….. 14
IV. NEXT STEPS & FUTURE OUTLOOK ………………………………………. 16
1: Through Phase 2 Completion………………………………………..………….. 16
2: Year 3 & Beyond………………………………………………………....……... 16
V. PERFORMANCE VERIFICATION & CHALLENGES …………………………. 17
1: Specifications……………………………………………………....…………..... 17
2: Assessment Challenges………………………………….………………………. 17
3: Navigational Challenges ……………………………………………….………...….... 17
4: Mobility Challenges…………………………………………………….……….. 18
VI. CONCLUSION ……………………………………………………………………... 19
VII. APPENDICES ……………………………………………………………………... 20

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TARRo2 DESIGN BRIEF 3
EXECUTIVE SUMMARY
This Design Brief describes Phase II of the Triage Assistance Rescue Robot (TARRo2) project
during the 2015­16 academic year. The purpose of this report is to provide the UCI Rescue
Robotics panel with sufficient information to assess the direction, implementation and
effectiveness of the TARRo2 system design developed by the Irvine Valley College (IVC)
Robotics Activity Group (RAG). The primary functional objective is to develop a device that
will autonomously locate and assess as many victims as possible on a field with dimensions
10,000 feet 2
within a 15 minute period. During the UCI competition, orange­colored buckets
simulate stationary human victims, and QR codes on each bucket contain information regarding
the victim’s status. During 2015­16 year, RAG has made considerable progress in advancing the
functional capabilities of TARRo2. The following six improvements have been implemented to
enhance the victim locational and assessment abilities of TARRo2:
1. A laser ranging sensor (lidar) and inertial measurement unit (IMU) provide
distance­to­victim data accurate to within 1 inch, enabling more accurate calculation of
relative victim position.
2. An LED array provides 300 lumens of light to assist cameras in detecting victims and in
reading QR codes.
3. To allow for a 180° field of view without interfering with the device’s direction of travel,
sensors are mounted atop a rotating turret.
4. TARRo2 data will be transmitted via WiFi to the First Responder Interface (FRI).
5. The First Responder Interface (FRI) will have a graphical user interface (GUI) that
livestreams data and video.
6. TARRo2 data is stored both onboard the device and in a database on FRI, benefiting first
responders and future implementation efforts of a multi­robot system.
To improve the maneuverability and search efficiency of TARRo2, four improvements have been
made:
1. A Navigation System complemented with GPS and ultrasonic obstacle detection
improves the capability to make real­time changes to the TARRo2 search strategy. The
first responder operator only needs to outline a desired search field, and TARRo2 will
then autonomously navigate through a set of generated waypoints within the field.
2. The device is supported by four wheels – two drive wheels and two casters. This design
improves control during turning and reduces axial loading.
3. Increased wheel size (6” vs. 4” in TARRo1) and more powerful motors (170lb. in. vs.
37.5lb. in.) assures the platform is able to move over uneven surfaces more reliably than
TARRo1.
4. A novel tire and wheel design prototyped using 3D printing allows the device to maintain
traction on a wider variety of surfaces.
To accommodate the increased size of RAG and the fact that several development teams needed
t o simultaneously implement and test various systems, TARRo’s Power and Structure Systems
changed in two main ways:
1. Additional sensor systems, communication devices, and larger motors required that the
power storage and distribution system be redesigned to include enhanced current flow
protection, better wiring harnesses, and improved safety measures.
2. The structure consists of three platforms that can be quickly assembled and disassembled,
allowing the team to independently test systems during integration.

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TARRo2 DESIGN BRIEF 4
I. CONFIGURATION DESIGN
The 2016 UCI Rescue Robotics Competition challenges teams to develop autonomous
navigation devices; each device must be capable of locating multiple victims in a field and
assessing each victim’s survival status. To simulate a real world scenario, orange buckets are
used as victims, and QR codes on each bucket provide status data. Performance is judged by the
amount of information returned at the end of a 15 minute survey on a grass and dirt field with an
area of 10,000 feet 2
.
TARRo2 autonomously provides critical and time sensitive victim information to first responders
during search and rescue operations. To accomplish this, TARRo2 has a structured hierarchy of
systems, each of which maximizes the effectiveness of the overall device. The hierarchy of
systems is:
I. Assessment ­ Sensors which locate victims and interpret status data.
II. First Responder Interface (FRI) ­ Communication between TARRo2 and first responders.
III. Navigation ­ Algorithms and computers that generate and communicate search paths to
Mobility System.
IV. Mobility ­ Mechanical and electrical drive components and suspension assembly.
V. Power & Safety ­ Batteries and electronics to store and safely distribute power to each
system.
VI. Structure ­ Supporting platforms designed for parallel system development and
packaging.
Figure 1.0: System Hierarchy
See Appendix B for a comprehensive system hierarchy structure.

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TARRo2 DESIGN BRIEF 5
1: Assessment System
The Assessment System autonomously detects and assesses victim status; it consists of four
sensors and supporting mechanical and computational components. Compared to TARRo1, the
TARRo2 Assessment System’s additional components allow for greater accuracy, increased data
acquisition speed, and assessment scanning motions to be independent of the device’s travel
direction.
The principle functional objectives for the Assessment System are:
● Detect the ‘distinguishing characteristics’ (visual spectrum) of a victim from a distance of
at least 20 feet in a dark environment.
● Detect the distance and direction between TARRo2 and victim to within 6 inches and 3°.
● Detect ‘health status’ information of a victim in a dark environment from a distance of 5
feet.
● Make status detections with 90% reliability within 5 seconds of coming within range of
the victim.
With regards to the UCI competition: the victim’s distinguishing characteristic is the bucket’s
orange color, and health status refers to data embedded in a 4” QR code.
To meet these functional objectives, TARRo2 incorporates the following design components:
● A color identification camera using computer vision identifies blocks of orange as
victims, then returns block size and relative horizontal position to a microcontroller.
● A laser ranging sensor (lidar) measures distances between TARRo2 and victims. Lidar
data is filtered through the microcontroller to eliminate statistical outliers.
● Two QR reading cameras mounted 7.75” apart, provide a broad perspective of the victim,
and increase the likelihood of quickly obtaining information as TARRo2 approaches
curved surfaces of the victims.
● LED headlights assist cameras with 300 lumens in dim and shadowed environments.
● Mounting the sensors on a servo driven turret enables 180° field of view that allows
scanning independent of TARRo2 direction of travel.
Combining GPS coordinates and headings generated from the Navigation System with lidar
range data allows TARRo2 to calculate lat/long coordinates for the victim location through the
following equations:
V lat. = T lat. + R/k * cos( + )
V long. = T long. + R/k * sin( + )
V, T are the coordinates of the Victim and TARRo2
R is the distance between TARRo2 and Victim
the IMU heading of TARRo2
the relative turret angle
k a scaling factor from inch to decimal degrees.

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TARRo2 DESIGN BRIEF 6
At this time, the data from the prototype indicate that the following performance specifications
will be achieved:
Victim characteristics range (orange blob detection) 25ft. max
Distance to victim accuracy < 2.5 in. typical
Status detection range with headlights only. (QR code) 5ft. max
Status capture and decode rate 30hz. typical
Future performance specifications will be improved through use of higher resolution camera
sensors and better optics. A scanning lidar unit will also provide TARRo2 with 360° field of
view and simultaneous “scan and assess” functionality. Forward looking infrared (FLIR) sensors
will provide real world victim identification and key biometric information.
Figure 2.0: Assessment Sensors

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TARRo2 DESIGN BRIEF 7
2: First Responder Interface
The First Responder Interface (FRI) System enables communication and remote control between
first responder operators and TARRo2. Compared to TARRo1, the TARRo2 FRI components
have enhanced control, increased communication range, and expanded the situational awareness
of operators.
The principle functional objectives for FRI are:
● Maintain a wireless connection up to 250 feet in open field, provided line of sight.
● Permit operators to generate and transmit autonomous search areas, remote control motor
signals, or stop operation commands.
● Stream live data and video to graphical user interface with less than one second latency.
● Record and store victim information onboard, pushing to FRI when WiFi is present.
To satisfy these functional objectives, TARRo2 utilizes the following design components:
● 2.4 GHz WiFi connection with 10 dBm antennas on robot and operator interface.
● 49 MHz analog remote control kill switch.
● Telemetry data and first person video data stream over WiFi.
● Onboard storage device with supporting sorting algorithm and database with shared
directory on operator interface.
At this time, data from the prototype indicates that the following performance specifications will
be achieved:
2.4 GHz Remote motor control range > 400 feet
2.4 GHz WiFi data range > 400 feet
49 MHz kill switch range 30 to 50 feet
Telemetry/Video latency 0.3 seconds typical
Directory sharing method SSH, auto­reconnect
Future performance specification will be improved through use of 5GHz WiFi frequency for
increased bandwidth and reduced signal interference. Further development of the GUI will
consolidate controls and information display.

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TARRo2 DESIGN BRIEF 8
3: Navigation
The Navigation System generates movement paths, obstacle avoidance strategies, and produces
mobility control signals. Compared to TARRo1, the TARRo2 Navigation System’s components
have led to smarter path planning, improved obstacle detection, and faster search capability.
The principle functional objectives of the Navigation System are:
● Generate a consecutive set of waypoint goals which fill at least 75% of a desired search
area.
● Detect obstacles > 3 inches and execute corrective avoidance maneuvers.
● Approach victims to within 5 feet to obtain status information, but avoid coming closer
than is necessary.
● Slow and stop motion (gracefully degrade) during loss of control signal.
To satisfy these functional objectives, TARRo2 utilizes the following design components:
● Mission planning software, GPS, and inertial measurement unit (IMU) based navigation
as implemented in an ArduPilot 2.6.
● Dual ultrasonic sensors determine obstacle presence and position.
● Proportion/Integral/Derivative (PID) feedback loop controller to control the approach to
victims.
● Automatic signal loss detection and control override.
At this time prototype performance measurement and testing is ongoing.
Search efficiency will improve through implementing simultaneous localization and mapping
(SLAM) functions with flood fill algorithms.

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TARRo2 DESIGN BRIEF 9
4: Mobility
The Mobility System, which moves TARRo2 about the field, consists of the mechanical and
electrical drive components. Compared to TARRo1, the TARRo2 Mobility System’s additional
components have led to improved reliability and increased terrain capability.
The principle functional objectives of the Mobility Subsystem are:
● Allow locomotion in tall grass, loose dirt and inclinations up to 20%.
● Traverse obstacles, made of various materials, up to 3 inches in height.
● Maintain a speed of 3 miles per hour on a level surface with a total weight of 50 pounds.
● Execute turns with a radius less than the width of the robot while bearing weight.
To meet these functional objectives, TARRo2 incorporates the following design components:
● Wide wheelbase (14” by 22”) improves weight distribution.
● Large and open tread tire design maintains traction and clears loose debris.
● Rocker suspension system for caster wheels assures 4 wheel support and enhances
traction and large obstacle traversal.
● High torque motors (170 lb.in.) with large wheel diameters (6”) increase weight capacity.
● Two drive wheels and two casters reduce axial loading while turning.
At this time, data from the prototype indicates that the following performance specifications will
be achieved:
Wheel Base 15.4 in. Payload Capacity 25 lbs.
Track 11.9 in. Top Speed 4 mph
Turning rad. 0.0 in. Obstacle Height 4 in. max
Weight 23 lbs. Max incline 38°
Max Torque 170 in. lbs. Max decline 37°
Max Power 0.107 hp Max roll angle 24°
Future performance specifications will improve as suspension systems are implemented on both
axles. Independent driving and turning of each wheel will increase terrain capability. Direct drive
brushless motors will improve efficiency and reduce weight and noise.
Figure 3.0: Suspension Articulation

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TARRo2 DESIGN BRIEF 10
5: Power & Safety
The Power and Safety System stores and safely distributes electrical power to other TARRo2
systems and safeguards. Compared to TARRo1, the TARRo2 Power and Safety System’s
additional components have led to improved safety, longer run time, and increased electrical
reliability.
The principle functional objectives of the Power & Safety System are:
● Distribute regulated voltage at 7.2 and 5.0 volts to components of all systems.
● Safe storage of energy for at least 60 minutes of nominal operation, and capability to
quickly restore after depletion.
● Protect components and environment in cases of short circuit, overvolt, undervolt, stall
condition, and impending danger.
● Immobilize TARRo2 remotely from at least 50 feet.
For the UCI competition: robot must be powered entirely by electrical power.
To meet these functional objectives, TARRo2 incorporates the following design components:
● Regulation and smoothing circuits provide consistent voltage despite varying current
demands.
● Quick disconnect wiring harness distributes power to individual components.
● Large capacity NiMH battery packs reduce battery swap downtime.
● Fuse block, voltage detection, bump stop, and remote kill protect TARRo2 from electrical
danger.
At this time, the data from the prototype indicate that the following performance specifications
will be achieved:
Energy 72 watt hours
Remote Kill Distance 53 ­ 28 ft. (environment dependent)
Energy Restoration Method Battery swap
Battery Specification 6 cell, 7.2v pack. 2 parallel packs
Run Time 60 minute (typical, Appendix C)
Future performance specifications will improve by implementing LiPo cells and onboard
charging circuits. Cell balancing and thermal regulation will prolong battery life and extend
operational runtime. Conformal coating of electrical circuits will provide additional
environmental protection.

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TARRo2 DESIGN BRIEF 11
6: Structure
The Structure System physically supports TARRo2’s onboard components. Compared to
TARRo1, the TARRo2’s additional assessment sensors have led to the introduction of additional
structural components. Overall TARRo2 now has increased component capacity, ease of
serviceability, and faster system development cycles.
The principle functional objectives are:
● Provide location and mounting provisions for electrical components, wire harnesses, and
mobility hardware for each of their necessary orientations.
● Facilitate simultaneous development and testing of TARRo2 systems.
● Support weight of structural components and additional payload while maintaining the
center of gravity within 2” behind drive wheel axis.
For the UCI competition: weight limit is 25 pounds, robot size limit is 24 inches wide by 24
inches long, and operates on a relatively flat grassy terrain.
To meet these functional objectives, TARRo2 incorporates the following design components
(Appendix F):
● Laser cut platforms enable component organization, wiring routes and mounting
provisions.
● A modular design with three standardized platforms permits rapid disassembly and
independent development of component systems.
● Weight biased component placement and CAD simulated platform loading.
At this time, the data from the prototype indicate that the following performance specifications
will be achieved:
Length 22.4 in.
Width 14.1 in.
Height 13.4 in.
Future performance specification will improve through better manufacturing methods and
materials. A casing will add aesthetic appeal while protecting the internal hardware of TARRo2
from environmental factors.

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TARRo2 DESIGN BRIEF 12
II. TEAM & FACULTY INFORMATION
The Irvine Valley College (IVC) Robotics Activities Group (RAG) is a subgroup of the Applied
Science and Engineering Club (ASEC), a noncredit extracurricular program at IVC. Lead by
Jonivan Artates (mechanical engineering, year 2), the 2016 RAG team is made up of:
● Jose Antelo, mechanical engineering, year 2
● Xochitl Alvarado, biomedical engineering, year 2
● Joe Wijoyo, computer science, year 2
● Brian Mauricio, electrical engineering, year 1
● Amal Eldick, chemical engineering, year 1
● Haowen Wong, electrical engineering, year 1
● Naziha Kibria, mathematics, year 2
● Wyeth Binder, civil engineering, year 2
● Sina Habibizad, biomedical engineering, year 1
The RAG members were divided into six different system teams, each in charge of different
aspects of the TARRo2 development process. The Structure and Integration team consists of
Jonivan and Naziha. Jonivan and Joe make up the Control and Communication team, Wyeth and
Joe the Assessment team, and the Navigation team consists of Jose and Amal. Xochitl and Sina
are in charge of Mobility, and Power is handled by Brian and Haowen.
ASEC RAG is led by faculty mentor Professor Jack Appleman. Other IVC faculty involved in
the development of TARRo2 are Professors Brett McKim, Iknur Erbas­White, Matt Wolken,
Brian Monacelli, Alec Sim, and Zahra Noroozi. The team receives funding and support from
Dean Corrine Doughty, Dean Lianna Zhao, and Merry Kim.

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TARRo2 DESIGN BRIEF 13
III. PROJECT ORGANIZATION & OUTREACH
The 2015­2016 academic year marks the second year of development on the TARRo project,
phase two of a three year plan. The goals of this endeavor were to provide hands­on experience
and application of classroom knowledge to a real world project. At the end of each academic
year, the team will compete with their robot in the ground rover division of the Rescue Robotics
Competition hosted by the University of California, Irvine (UCI).
The 2015­16 academic year’s team began with three members, all of whom returned for their
second year on the project. Presentations were made in STEM classes and clubs to promote the
project to other students. Additionally, RAG demonstrations were hosted by IVC administration
to promote the endeavor to faculty of the college and district. Prospective members submitted
applications, and selection was based on academic potential, previous experience, and an
expressed passion for robotics and its applications; five additional members were brought onto
the project during the fall semester.
The first four months served as a training period which allowed members to expand their
knowledge base and skillsets. During weekly RAG meetings, members developed a foundation
in the study of robotics, studying aspects of mechanical and electrical engineering, computer
science, as well as applicable concepts in fabrication and economics. Additionally, guest
lecturers were hosted throughout the year, including faculty experts in various fields: Photonics
from Professor Brian Monecelli, Differential Global Positioning System (DGPS) from Professor
Matthew Wolken, and Rapid Prototyping from Professor Brett McKim. Through the winter,
weekly time commitments were ramped up to three meetings a week, and membership increased
to eleven.
Over winter break, the project began the iterative “Design, Build, Test” process of the TARRo2
project. Group meetings were held on a weekly basis in order to monitor progress and to manage
resource allocation. In addition, means for online communication were implemented for an open
forum style of documentation archiving. The transparency created between system development
teams allowed for reduced iteration cycles, assisting the integration processes. Additionally, the
RAG team incorporated community outreach as an integral part of development. Members
benefitted through various opportunities of interaction with industry professionals and academic
mentors, and served as IVC ambassadors to intramural and extramural robotics and STEM
events. This year, RAG has participated in or attended events such as the DARPA DRC, IEEE
chapter STEM expo, Maker­Faire mini, and the MD&M West manufacturing expo. The team has
also presented to multiple local high schools and colleges throughout the 2015­16 year.
1. Timeline
During the initial training period, Management team members organized the scope, time, quality,
and budget resources in order to construct a success criteria for the TARRo2 project by the end
of the academic year. Based on this projection, tasks and deadlines were laid out in
reverse­chronological order. This was mapped using a Gantt chart, allowing a critical path, team
resources, and subsequently, task priorities to be mapped out ( Figure 4.0 ). Milestones were
placed at the projected completion date of each system, and marked the beginning of integration
with other systems. The time frames for each task were used as a reference from which managers

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TARRo2 DESIGN BRIEF 14
could track development progress. Reallocation of resources permitted flexibility in meeting
milestone dates. During the development phase, emphasis was placed on documentation of
individual tasks. These files were available to the entire team, and were used to determine how
parallel developments would integrate. Clearly defined inputs, outputs, functionality, and
constraints were created for each component, system, and the project as a whole. By design,
these boundaries were established to mesh cleanly with their respective neighbors from the
physical, electrical, and programming aspects. Once development was complete, system
integration connected the various chains of inputs and outputs. The expanding systems were
frequently tested during the integration period to facilitate debugging subtle inconsistencies and
runtime errors.
Figure 4.0: Tasks and subsequent integration phases.
2. Marketing
The long term vision of this project is to develop a commercially viable device capable of
assisting first responders in an emergency structural collapse disaster. In developing a plan to
market, the current state of robotics technology, industry and markets are of prime consideration.
The complex marketing strategy of TARRo addresses several factors:
1. A small niche customer base that would likely purchase response devices.
2. Large upfront costs to ownership and ongoing routine service costs.
3. Unpredictable product demand that relies on environmental disaster situations.
4. Wide range of environments and tasks that TARRo must be able to manage.
The team developed a number of commercialization strategies, seeking to maximize product
value.
Inspired by the successful commercialization of the iRobot Roomba “vacuum robot,” the RAG
team anticipates that a TARRo V1 could be implemented to provide after­hours surveillance of
large structures to supplement stationary video and fire detection systems (Appendix A). This
enables the TARRo customer base to become accustomed to TARRo V1 before an emergency
situation occurs. Utilizing the onboard assessment sensors and WiFi connectivity, TARRo V1
data regarding the building structure, total individuals present, and robot status would be

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TARRo2 DESIGN BRIEF 15
collected; all information is sent to a remote interface and transmitted into a cloud storage and
analysis system accessible by public first responder agencies. This feature would scale with
additional robots, allowing multiple floors or areas to be covered simultaneously. The presence
of TARRo security will increase the safety of TARRo­surveilled areas without unnecessarily
risking the lives of security guards. In the event of a natural disaster, surviving TARRo devices
could relay live streams of time­critical data, crucial for saving lives and effectively managing
first responder resources.
The reason for developing TARRo V1 for the the surveillance and security market is its size.
This market is more mature than the disaster response robotics segment, and valued to reach $42
billion versus $1 billion respectively within the next 8 years, respectively (Appendix A).
To offset the upfront costs of ownership tied to robotic systems, TARRo would be provided as a
data subscription service. Data from TARRo would be wirelessly uploaded to a server over,
which provides data processing specific to customer needs. Services would include crowd
analytics, traffic management, and structural information in addition to first responder assistance.
Additionally, TARRo’s software systems would be managed through this connection, allowing
for remote troubleshooting and firmware update capabilities.
To further reduce customer operating costs, the team has focused on a modular design for all
systems. This allows the customer to have a system that is tailored to their needs without
excessive complexity or expense that is typical of off­the­shelf robot solutions. In emergency
situations, TARRo seeks to provide a comprehensive assistance system. Applications include
attaching the Assessment System to an off the shelf drone for aerial search and rescue, or using
the Mobility System to tow aid through rough terrain.
The expectations of an effective general disaster response robot are difficult to define, and are
usually redefined “in the moment.” In contrast, robot systems need functionality that is defined
specifically, which is then followed by a long development time frame. TARRo minimizes this
disparity through a development cycle focused on the most current standards and an expandable
system design. The National Institute of Standards and Technology (NIST) has published
Standard Test Methods for Response Robots (Jacoff, Appendix A) to which TARRo V1 will use
as a performance baseline. Using these quantified performance merits, a customer would be able
to make informed decisions in choosing a robot. Beyond these standards, additional systems will
be designed to plug and play, quickly and easily adding specific functionality. This way,
customers would be able to start with a version of TARRo that is sufficient to their needs, and
add­on as necessary, eliminating the costly cycle of acquiring and testing multiple platforms.

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TARRo2 DESIGN BRIEF 16
IV. NEXT STEPS & FUTURE OUTLOOK
1. Through Phase 2 Completion
The development of TARRo2 has required the introduction of several technologies, including the
navigational unit, lidar, and tire design. The use of a navigational unit has greatly improved path
planning, and its integration with computer vision and lidar technologies has improved the
Assessment and Mobility Systems. The shift to urethane­casted wheels and a rocker suspension
for the rear caster wheels increases TARRo2’s range of mobility, allowing it to more effectively
assess victims in a disaster. Additionally, this year’s team was restructured by treating the various
systems in a modular fashion. Streamlining development, testing, and system integration
benefited the team dynamic and increased member productivity.
2. Year 3 & Beyond
Looking ahead to TARRo3 development, the team hopes to implement several new technologies
to further improve functionality. In order to better locate and identify victims in a structural
collapse disaster, a thermal imaging sensor will be integrated, expediting the recognition process.
Known as Forward Looking Infrared (FLIR), this sensor will allow the Assessment System to
more efficiently locate human targets, which are identified by unique heat signatures. This, in
turn, will alleviate pressure on the subsequent systems, making for a more efficient product.
Another sensor that would benefit TARRo is a scanning lidar unit. As the demand for these
sensors increase, new manufacturing methods and economies­of­scale has greatly reduced prices.
Implementing this sensor would enable Simultaneous Localization and Mapping (SLAM). This
functionality would provide significant gains to the value and capability of the TARRo system.
To take advantage of SLAM technology, the team plans on introducing flood fill algorithms to its
Assessment and Navigation Systems. This would autonomously generate search waypoints
within a prescribed field.
By using such an algorithm, flood fill will allow TARRo to retain the positional coordinates of
visited locations, ensuring that while scanning for targets, the same geographic location is not
visited twice. Once again, this allows for a dramatic increase in efficiency and frees up time and
resources that can lead to TARRo assessing a wider geographic area.
Lastly, the team hopes to develop a means for a multi­robot system in the near future. Deploying
multiple mobile units or a mobile unit communicating with fixed surveillance units would
increase data throughput and create the possibility for exponential growth in every area of
functionality. An expanded FRI would allow multiple robots to communicate with one user
interface; the consolidation of multiple data inputs into a network allows for better
decision­making and machine learning over time.

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TARRo2 DESIGN BRIEF 17
V. PERFORMANCE VERIFICATION & CHALLENGES
1. Specifications
The current performance specifications (listed below) were determined empirically during the
integration and testing phases of the TARRo2 project and will be further updated in coming
weeks.
Length 22.4 in. Top Speed 4 mph Energy 72 watt hours
Width 14.1 in.
Obstacle
Height 3 in. max Protection
Fused, Switch, Low
Voltage
Height 13.4 in. Run Time 60 min. (typ.) Remote Kill dist.
53 ­ 28 ft. (env.
dependent)
Wheel
Base 15.4 in. Max incline 38 deg. Remote Mobility Line of Sight
Track 11.9 in. Max decline 37 deg. Charge time ~130 min.
Turning
rad. 0.0 in. Max roll angle 24 deg Wireless Freq. 2.4 GHz
Weight 23 lbs. Max Torque 150 in. lbs. Onboard Storage 16gb, expandable
Payload 25 lbs. Max Power .107 hp Suspension Rocker, Non­damped
2. Assessment Challenges
The original plan for victim assessment in TARRo2 was to wirelessly stream the video feeds to
FRI, where QR detection algorithms would be performed. This method was initially chosen for
two reasons:
1. Computationally heavy tasks would be performed in stationary locations, with more
computing power.
2. Cost of each additional robot would be reduced in a multi­robot system.
Video transmission and QR detection were successfully developed and tested during the build
phase. During integration however, it was found that the 2.4 GHz control radio communication
signal would interfere with the 2.4 GHz WiFi connection between the robot and FRI. Though it
was possible to operate the robot without the need for control radio, members decided that a
different solution should be found, as the radios of other teams would similarly interfere during
competition. This issue was resolved by moving the QR detection software onto the robot, and
only updating FRI while WiFi was available. Operator awareness of victim detection is
compromised, but TARRo maintains overall performance as determined during field testing.
3. Navigational Challenges
During the 2015 Rescue Robotics Competition, it was noted that TARRo1, and other ground
rover devices faced navigational issues in every trial. Guided solely by navigating to nearby
victims, TARRo1 routinely became trapped in “local minimums,” recursively visiting the same
group of victims. Runs were limited on time, so human intervention was required to break out of
the minimums. During the design phase of TARRo2, it was determined that a system designed to
autonomously break local minimum issues would be a priority. Research and ideation was

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TARRo2 DESIGN BRIEF 18
completed on various positioning systems, including WiFi positioning, Bluetooth beacons, dead
reckoning, and one novel approach using concepts from a sextant in celestial navigation.
Included in these discussions were possible combinations of the systems to offset the inherent
shortcomings of each. This would be accomplished through the use of Kalman filters, which
develop error covariances with sensor’s sampling data to increase state estimation accuracy. As
the complexity of the navigational challenges, along with those of the other systems increased,
the practicality of dedicating resources to this effort within the given time constraints diminished.
It was decided that an off the shelf navigational unit would provide the solution for this stage of
TARRo development, and consequently the ArduPilot 2.6 was chosen as the main navigational
device.
4. Mobility Challenges
The product of last year, TARRo1, received a “Did Not Finish” (DNF) at field trials due to a
fault in the Mobility System. A Terminal Fault Analysis completed on TARRo1 determined that
the friction­based motor housing did not hold up to the cyclical torque applied by the motors in
the terrain of the competition (Appendix G). TARRo2 remedies this issue with a new drive
configuration, including interference fit motor mounts. The design goal of this year’s Mobility
System is to maintain contact of all wheels to the ground whenever possible, ensuring traction of
the drive wheels in as many terrain conditions as possible. The final design utilizes a rocker
suspension for the caster wheels at the rear of the platform, facilitating passing over obstacles of
up to 4 inches while maintaining contact of all four wheels. Drive wheels were reduced from four
to two and placed at the front of the robot bearing the majority of the weight. A single axis was
chosen to reduce drag during turning and allow encoders to more accurately represent vehicle
movement. Testing has determined that moving the center of rotation to the front of the robot
best complements the inputs from the Navigation System. In certain situations, namely hills with
loose or slippery terrain, it was found that smooth rubber tires failed to maintain traction. This
was resolved by using a wider tire design with deep reliefs in the tread. The larger contact area
prevented the tire from “digging” into loose terrain, while the reliefs work similar to a paddle,
providing traction in difficult situations.

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VI. CONCLUSION
In the development of TARRo2, RAG invested a considerable effort to ensure a holistic approach
to the challenge of rescue robotics. Going beyond building an autonomous robot to complete a
single task, the team focused on the ecosystem in which a robot of this nature would ultimately
function. This led to studies beyond the engineering and computer science topics that generally
encompass robotics. The goal in this effort was to truly determine the primary functionality of
the TARRo system, the scope which would dictate the direction of project. Answering this
question required the team to expand their learning into subjects such as economics, sociology,
history and ethics. This mindset permeated throughout the development cycle, shaping priorities
and serving as a prime directive in the various decision making processes. During the design and
construction phases of TARRo2, the various system teams gained experience in communication
and interaction with members of other systems, on whom they depended on for cohesive inputs
and outputs. These lessons serve to benefit the team in future projects where progress relies on
the combined efforts of each individual. During this year, the members of RAG successfully
completed the design, construction, integration and testing of TARRo2 . Equally as beneficial, the
team gained first hand experience learning from mistakes, applying textbook knowledge to a real
world project, and growing through self­driven discovery.

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VII. APPENDICES
TABLE OF CONTENTS Pg #
Appendix A: Works Cited……………………………………………………………. 21
Appendix B: TARRo2 Systems Map…………………………………………………. 22
Appendix C: TARRo2 Power Accounting…………………………………………… 23
Appendix D: Battery Capacity Testing……………………………………………….. 24
Appendix E: Bill of Materials………………………………………………………... 25
Appendix F: Weight Analysis……………………………………………………….... 26
Appendix G: Failure Analysis of TARRo1…………………………………………... 27
Appendix H: Table of Acronyms …………………………………………………….. 30

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APPENDIX A ­ Works Cited
iRobot History. (n.d.). Retrieved April 02, 2016, from
http://www.irobot.com/About­iRobot/Company­Information/History.aspx
Jacoff, A. (2013, October 1). Standard Test Methods For Response Robots. Retrieved February
20, 2016, from
http://www.nist.gov/el/isd/ks/upload/DHS_NIST_ASTM_Robot_Test_Methods­2.pdf
SSI Staff. (2014, May 15). Report: Video Surveillance Market to Reach $42B by 2019. Retrieved
March 15, 2016, from
http://www.securitysales.com/article/report_video_surveillance_market_to_reach_42b_by_2019
Service Robot Statistics. (n.d.). Retrieved March 16, 2016, from
http://www.ifr.org/service­robots/statistics/

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Appendix B ­ TARRo2 Systems Map

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Appendix C ­ TARRo2 Power Accounting
The voltages used for each component were determined using the specifications in the respective
datasheets. In cases where a component was compatible with a range of voltage levels, the
appropriate selection was made from the three levels available on TARRo2: 7.2v, 5v, or 3.3v. A
multimeter was inserted in series with the component circuit to determine current draw during
testing. Values provided are the typical consumption. Text in red were not empirically tested by
RAG; those current values were provided by manufacturer datasheets.

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Appendix D ­ Battery Capacity Testing
A 6­ohm, 50 watt resistor was attached to a battery, along with a multimeter attached in parallel.
Voltage measurements were taken at 5 minute intervals, and current was derived using Ohm’s
Law. A Riemann sum was taken of the current * time, used to estimate the area under the curve,
the capacity of the battery. The particular battery shown is a 2 year old 7.2v Tenergy model, rated
at 4200mah. The data shows the battery’s voltage dropping off after discharging only 1800mah,
indicative of a dying battery. Following this test, new batteries with 5000 mah capacity were
purchased.

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Appendix E ­ Bill of Materials
The Bill of Materials (BOM) was used to catalog the various components and current market
prices during the build of TARRo2. The following BOM is of the final components to be used
during competition. Various consumables are not noted as they were considered stock to RAG.
This included fastening hardware, wire, laser cut material, and 3D printing filament.

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Appendix F ­ Weight Analysis
The weight analysis table was populated during the construction phase of the TARRo2 project.
Consideration to the benefits of performance were weighed against the weight penalty of each
component, specifically in the selection of drive motors and batteries. Additionally, the table is
divided into each platform level, which assisted in choosing component placements that would
best benefit TARRO2’s center of gravity.

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Appendix G ­ Failure Analysis of TARRo1
Failure Analysis of TARRo1
By: Jonivan Artates
For: 2015 ASEC Robotics Team
Abstract:
On May 31, 2015 TARRo competed at the UCI Rescue Robotics Competition in Aldrich
Park. During the first run, it was noted that TARRo had difficulty turning and one of the driven
wheels had stopped in providing propulsion to the robot. TARRo was withdrawn from the
competition before a second run was attempted in order to minimize hardware loss. A post event
investigation suggests that a pinch bolt holding the left rear motor, lacking sufficient torque to
constrain the motor, was the single­point failure (SPF) which caused a cascade failure to TARRo.
Observations:
May 31, 2015 UCI Rescue Robotics Competition
­ During run one, TARRo lacked sufficient torque to turn under own power
­ During run one, TARRo had only one of two wheels on the left side rotating
­ Proceeding run one, while on a bench, TARRo was unable to drive the rear left wheel, while the
front left, wired in parallel was driven (wheels unladen)
June 9, 2015 Competition Debrief
­ Testing each of the four motors, each had a resistance similar to the others except the left rear,
which had an open circuit (infinite resistance)
­ While removing the pinch bolts securing the motor to the mount, it was noted that they were
easily loosened using an allen wrench; only slightly tighter than finger tight

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Figure 1: Assembly of motor and mount into chassis
­ While removing the motor, the motor leads had been twisted together and the red wire had
become disconnected from the motor tab at the solder joint. The red motor lead was bent in the
direction of the lead, as shown:
Figure 2: Motor leads and tab
­ Applying electricity directly to the motor drove the output shaft

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TARRo2 DESIGN BRIEF 29
Analysis:
The cause of the open circuit was a break at the joint where the red lead was soldered to
the motor lead. The cause of the break seemed to have been through the wire leads twisting and
causing excessive force at this joint. The bent motor lead supports this hypothesis.
The twisting of the wire leads would be the result of the motor rotating in its housing,
while the wheel and wire leads were fixed. The method of securing the motor in the housing is to
pinch the motor in a cylindrical mount, with cutouts on opposing sides (see Figure 1). As the
inner diameter (ID) of the mount is larger than the outer diameter (OD) of the motor, pinch bolts
are used to close the gap then increase the frictional force between the smooth plastic mount and
the smooth metal motor casing. This system lacks a key to interfere with motor rotation. Without
adequate torque on the pinch bolts, the motor can rotate within the housing if the wheel applies a
greater moment than the housing. The ease of removal of these bolts indicates that the torque on
the pinch bolts was less than necessary to fix the left rear motor.
Other Considerations:
1) Installing suspension on TARRo would allow more driving wheels to be in contact with the
ground at a time, reducing the power and therefore moment each motor undergoes to drive the
robot.
2) Reducing the weight of TARRo would reduce the power consumption of each motor and
therefore moment each motor undergoes to drive the robot.
3) Additional driven wheels would reduce the moment on each individual motor.

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Appendix H ­ Table of Acronyms
A ­ Amps IVC ­ Irvine Valley College
ASEC ­ Applied Science and Engineering
Club
MDF ­ Medium density fiberboard
BOM ­ Bill of Materials NIST ­ National Institute of Standards &
Technology
DNF ­ Did Not Finish NiMH ­ Nickel Metal Hydride
DGPS ­ Differential Global Positioning
System
OD ­ Outer diameter
ESC ­ Electronic speed controller PID ­ Proportional­integral­derivative
EMI ­ Electromagnetic interference PWM ­ Pulse width modulation
FDM ­ Filament deposition modeling RAG ­ Robotics Activities Group
FRI ­ First Responder Interface SLAM ­ Simultaneous Localization and
Mapping
FLIR ­ Forward Looking Infrared SPF ­ Single­point failure
GPS ­ Global Positioning System TARRo ­ Triage Assistance Rescue Robot
IMU ­ Inertial measurement unit UCI ­ University of California, Irvine
ID ­ Inner diameter