Future of Robotics Technology.pptx

1. The Future of Robotics Technology
2. Will Robot Take Our Job?
3. The Jobs Landscape in 2022 Source: Future of Jobs Report 2018, World Economic Forum
4. 2022 Skills Outlook Source: Future of Jobs Report 2018, World Economic Forum
5. This affects social & economic sectors Physical Digital Biological Different technologies are coming together (convergence) This is bringing different areas together The way we work, buy and sell things The way we travel The way we live 4th Industrial Revolution: What is Happening?
6. Robotics Artificial intelligence Self driving cars Virtual reality 3D printing Internet of Things (IoT) Bioengineering Metadata & analytics Digital currencies and blockchain Quantum computing Technology Trend
7. What is a Robot? • A robot is a machine — especially programmable by a computer — capable of carrying out a complex series of actions automatically. • A robot is a machine designed to execute one or more tasks automatically with speed and precision. • A robot is an active artificial agent whose environment is the physical world. • A robot is a programmable, multifunction manipulator designed to move material, parts, tools or specific devices through variable programmed motions for the performance of a variety of tasks.
8. Robotics – A Multidisciplinary Approach
9.  Ability to learn  Ability to reason  Ability to use language  Ability to formulate original ideas Robotics and Artificial Intelligence
10. Robotics and AI • Robots and AI bring exciting opportunities to industries, promising to make our future more automated and efficient. • With advances in robotics and artificial intelligence continuing to surprise us, there probably is not a single industry being left untouched by these technologies. • The robot market is now projected to reach a value of $77 billion by 2022, more than double its size in 2017. • AI is developing even faster. It grew from $700 billion in 2017 to $1.2 trillion in 2018 and is expected to be worth $3.2 trillion by 2022. • Clearly, both robotics and AI are powerful markets, and the combination of these two technologies can change our lives for the better.
11. Machine Learning
12. Robot Vision
13. Natural Language Processing
14. How Robotics Could Transform our Future
15. Security never sleeps: Robotics and AI in public safety • AI-based drone will be used for automatic recognition of suspicious activities. • This drone will be able to predict and detect crime. • This technology will change society in a very important way: it will allow law enforcement officials to act quickly whenever a suspicious behavior has been spotted.
16. Robots in Education • Robots will boost the process of personalized learning. • Children with autism will learn communication and social skills and students with developmental issues and attention disorders will learn focus from specialized humanoid robot.. • AI robots will soon teach English in Japanese schools. AI robots will help students to improve their listening, speaking, reading and writing skills. Such tech would be especially useful in remote areas where schools do not have enough language teachers.
17. Robots at Home • Cloud-connected home robots are likely to evolve into more advanced version. • Home robots with speech comprehension and increased interactions with humans in the upcoming years. • Robotic cookers will be able to use crowd-sourced knowledge.
18. Cobot: Robots as Coworkers • Robots will have a profound effect on the workplace of the future. They'll become capable of taking on multiple roles in an organization, so it’s time for us to start thinking about the way we’ll interact with our new coworkers. • The machines will likely evolve more in terms of voice recognition.
19. Could you Answer to a Robot Boss? Source: Study conducted by Oracle and Future Workplace
20. Autonomous Cars • We’re getting closer to the day when the self-driving cars will not require any human intervention. • The perception of this technology among the public went • from “How is it even possible?” • to “Maybe it’s possible...” • to “Definitely getting there!”
21. Healthcare robots
22. Nanorobots • Robotic devices able to perform tasks at the nano scale (i.e., scale of a nanometer) are called “Nano Robots.” • A nano meter is a billionth of a meter, that is, about 1/80,000 of the diameter of a human hair, or ten times the diameter of a hydrogen atom. • Fully functional, autonomous nanorobots with completely artiﬁcial nano components have not been realized yet.
23. Robots to Fight Against Covid-19 5G smart patrol robot at Guiyang Airport, China Robot Tommy at hospitals of Italy UVD Autonomous disinfection robots
24. Robots to Fight Against Covid-19 Keenon Delivery Robot Zipline Delivery Drone
25. GPU-Accelerated Latte Making Robot
26. Stages in the Path of Robotics Beginner Intermediate Advanced
27. Beginner You first need to have • Curiosity • Willingness • Passion
28. Beginner (cont…) • Basic programming Knowledge (C/C++ is a good start) • Basic Electrical & Electronics Knowledge (Current, voltage, Resistance, sensors, motors etc.)
29. Beginner (cont…) • Arduino Basic/Starter Kits* • Play around sensors, motors, LEDs and LCD • Build some mini projects like ◦ Mini calculator ◦ Digital Clock ◦ Smart Blind Stick ◦ Line and Wall following Robot *most common, but LEGO, ARM, PIC, AVR kits are also good
30. Intermediate • Primary skills and knowledge ◦ Linear Algebra ◦ Digital Logic Circuit ◦ Image Processing ◦ Basics of Robot Motion ◦ Higher Level Programming Language (Python, MATLAB etc.)
31. Intermediate (cont..) • Build your projects with Raspberry PI • Projects: ◦ Robotic Arm ◦ Aerial Robotics ◦ Remotely Controlled Robots ◦ Semi or Full Autonomous Robot ◦ And Many more …
32. Intermediate (cont..) • PCB Designing • Robot Designing  AutoCAD  SolidWorks • Simulation RoboDK Webot Gazebo • 3D Printing
33. Advanced Level • Artificial Intelligence • Computer vision • Machine Learning • Control Algorithm • Human-Robot Interaction • Robotic Operating System (ROS) • Embedded systems • Robot Localization • Planning • Navigation
34. Learning Resources • Youtube • Arduino forum (https://forum.arduino.cc/) • Instructables (https://www.instructables.com/) • Robotics Book • Project Guided Books • Blogs and Forums • Online courses (Coursera, mit opencourseware, edX, udemy etc.) • Workshops • Webinars (New Normal)
35. Basic List of Resources (Just Example. Don’t Limit to these Resources Only) • AutoCAD: https://thesourcecad.com/autocad-tutorials/ • SolidWorks: https://www.lynda.com/SOLIDWORKS-tutorials/SOLIDWORKS-Design- Mechatronics/765317-2.html • RoboDK: https://robodk.com/examples#examples-spotweld • Webots: https://cyberbotics.com/doc/guide/tutorials • Arduino: https://www.youtube.com/watch?v=tzNROquPEHQ&list=PL1KVSZBJtW0pBFu379TuXztnFIB2rmc tK • Raspberry Pi: https://pythonprogramming.net/introduction-raspberry-pi-tutorials/ • Python: https://www.tutorialspoint.com/python/index.htm • CNC: https://www.cnccookbook.com/learn-cnc-basics-tutorial/ • Reinforcement Learning: https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PLqYmG7hTraZDM- OYHWgPebj2MfCFzFObQ • 3D Printing: https://www.coursera.org/learn/3d-printing-revolution#syllabus • Artificial Intelligence: https://www.udacity.com/course/intro-to-artificial-intelligence--cs271
36. Stay Safe! Thank You!

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The size related challenge is the ability to measure, manipulate, and assemble matter with features on the scale of 1 to 100 nm.
Give example
DU Salary Automation
Job transformation of Typewriter operators
One set of estimates indicates that 75 million jobs may be displaced by a shift in the division of labour between humans and machines, while 133 million new roles may emerge that are more adapted to the new division of labour between humans, machines and algorithms.

By 2022, no less than 54% of all employees will require significant re- and upskilling. Of these, about 35% are expected to require additional training of up to six months, 9% will require reskilling lasting six to 12 months, while 10% will require additional skills training of more than a year.

Give example of pandemic time, the best workers are not terminated! Need to have multiple skills! Need skill transformation!
Give example of pandemic time, the best workers are not terminated! Need to have multiple skills! Need skill transformation!
The 4IR is bringing technologies that blur the lines between the physical, digital and biological spheres across all sectors.
Technologies like artificial intelligence (AI), nanotechnology, quantum computing, synthetic biology and robotics will all drastically supersede any digital progress made in the past 60 years and create realities that we previously thought to be unthinkable. Such profound realities will disrupt and change the business model of each and every industry.

The pandemic pushes us to 4IR
Every day, more manual processes become automated, and as technology continues to accelerate, so will automation. As a result, the world of work and labor market demand are rapidly changing. According to McKinsey, up to 375 million workers may need to change their occupational category by 2030, and digital work could contribute $2.7 trillion to global GDP by 2025.
Robots can be guided by an external control device or the control may be embedded within.

Robots may be constructed on the lines of human form, but most robots are machines designed to perform a task with no regard to their aesthetics.
It is a multidisciplinary field that combines mechanical engineering, electrical engineering, and computer science but also draws on disciplines such as psychology, biology, neurology, sociology, and mathematics. To get a robot to do even simple actions often requires solving several challenging problems at once across multiple areas of study.

Cognitive Science: the study of thought, learning, and mental organization, which draws on aspects of psychology, linguistics, philosophy, and computer modelling.

Intelligent Robotics combines
Artificial Intelligence
Natural Language Processing
Machine Learning
Autonomics
Machine Vision
Artificial intelligence is the most exciting field in robotics.
Like the term "robot" itself, artificial intelligence is hard to define.
Intelligent robot is a man-made machine with our intellectual abilities.
Any computer program that shows characteristics, such as self-improvement, learning through inference, or even basic human tasks, such as image recognition and language processing, is considered to be a form of AI.

Weak Artificial IntelligenceThis type of AI is used to create a simulation of human thought and interaction. The robots have predefined commands and responses. However, the robots do not understand the commands they do only the work of retrieving the appropriate response when the suitable command is given. The most suitable example of this is Siri and Alexa. The AI in these devices only executes the tasks as demanded by the owner.
2. Strong Artificial IntelligenceThis type of AI is used in those robots who perform their tasks on their own. They do not need any kind of supervision once they are programmed to do the task correctly. This type of AI is widely used nowadays as many of the things are becoming automated and one of the most interesting examples is self-driving cars and internet cars.
Machine learning is fundamentally set apart from artificial intelligence, as it has the capability to evolve.

Using various programming techniques, machine learning algorithms are able to process large amounts of data and extract useful information. In this way, they can improve upon their previous iterations by learning from the data they are provided.

Process of automatically discovering patterns in data.
Once discovered, the pattern can be used to make predictions.
Applications: Fraud Screening, Sales Forecasting, Inventory Management, Public Health
Supervised learning is the process of an learning(from the training dataset) can be thought of as a teacher who is supervising the entire learning process. Thus, the “learning algorithm” iteratively makes predictions on the training data and is corrected by the “teacher”, and the learning stops when the algorithm achieves an acceptable level of performance(or the desired accuracy).
Has training dataset.
Example: sort banana, apple and grapes from a basket where each object is trained before.

In unsupervised learning, there is no correct answer and there is no such teacher(unlike supervised learning). Algorithms are left to their own devises to discover and present the interesting structure in the data.
Example: sort banana, apple and grapes from a basket where there is no training.

In reinforcement learning, there is no answer but the reinforcement agent decides what to do to perform the given task. In the absence of a training dataset, it is bound to learn from its experience.
Example: Chess, Find shortest path
Ability of robots to identify objects, scenes and activities in image
Uses sequences of image-processing operations and other techniques to break the task of analyzing images down into manageable pieces
use cameras to handle complicated tasks and make sure that the desired activity is performed as intended. Various types of cameras are used, starting from regular RGB cameras, LIDAR scanners, IR cameras, depth cameras and more.
Industrial robots perform assembly and “pick and place” tasks. They use machine vision algorithms to locate and arrange parts and verify operations like welding.
Robots in retail can be found in the aisles of department stores and in the warehouse. The former, the aisles robots, have a friendly shape of human or very similar to it. They perform both customer guidance and shelf management. Machine vision algorithms such as face recognition and object classification are used. Warehouse robots use object detection and navigation algorithms.
Example of motion detection
Ability of a computer to interpret human language and take appropriate action
Siri for iphone

Chatbots are capable of understanding text written in natural language and responding with answers to basic questions and problem resolutions. Some bots are equipped with NLP so intelligent that humans can’t distinguish if they are humans or robots.
My hotel booking experience.

Healthcare physicians spend more time filling health record documents than they they do consulting with patients. The medical industry serves serves billions of people a year. To prioritize time, prevent burnout for physicians and provide patients with better healthcare, AI technology powered by natural language processing can assist with dictating observations and details that will automate filling in the EHR.
The Los Angeles Police department handles car bombs with a 50-foot telescoping arm on their burly Bomb Assault Tactical Control Assessment Tool (BatCat), built on a Caterpillar tractor chassis.
In Cleveland, a tiny version, the 12-inch robot Griffin, that under cars and behind dumpsters to scan for hidden explosive devices.
A police robot has been deployed to patrol areas of Tunisia's capital to ensure that people are observing a coronavirus lockdown.
NAO, the humanoid robot, is already forming bonds with students from around the world.
The line between classrooms and individual learning settings is already starting to blur. As Kendra Roberts, an educational expert from Essays.ScholarAdvisor, explains, “A single teacher does not have the capacity to meet the needs of personalized learning for every single student in the classroom. Computer-based learning is already changing things in that matter. It’s not replacing the teacher, but it enables students to learn at their own pace.”
AI robots will soon teach English in Japanese schools
AI robots will help students to improve their listening, speaking, reading and writing skills. Such tech would be especially useful in remote areas where schools do not have enough language teachers, or lack funds to hire them.
Cloud-connected home robots are already becoming part of our lives. We can set up the vacuum cleaner to do the chore for us, and we can schedule a warm home-cooked meal to be ready by the time we’re finished with work. Multi-function robotic cookers are able to fry, steam, bake, slow cook, and perform any other action without our intervention. We just set them up.
These cloud-connected robots are likely to evolve into more advanced version. We expect to see speech comprehension and increased interactions with humans in the upcoming years. These developments may end up changing the entire look and feel of our homes!
Collaborative robots to pick plants
Surgery with cobots
Burger flipping cobot
Cobot co-pilot

GROWBOT uses a Sawyer cobot arm to help greenhouse workers pick plants. (Credit: Rethink Robotics)
The GROWBOT (Grower-Reprogrammable Robot for Ornamental Plant Production Tasks) project at King’s College London is using a Sawyer cobot arm to help greenhouse workers pick plants. GROWBOT is intended to let non- expert users work with robots for repetitive tasks and to help relieve shortages of seasonal labor. It uses machine learning to flexibly automate the handling of seedlings, herbs, and other plants.

Researchers at Nottingham Trent University (NTU) are developing “Scoliobot” for precise spinal surgery. They are currently working on 3D-printed models with two UR5 cobots from Universal Robots. The team is also using augmented reality to provide surgeons with live feedback. One robot arm, dubbed the Datum Robot, would follow a patient’s spine and collect data on how he or she moves. The other, called the Tooling Robot, would automatically adjust to drill holes itself for realignment rods to be placed in vertebrae.

As robots move from food processing into restaurants, the equipment must still be clean, consistent, and efficient. Miso Robotics’ Flippy uses a cobot arm with a variety of end-of-arm tools, its Miso AI platform, and cloud-based monitoring functions.
The burger-flipping robot can work on a grill or fryer, comply with OSHA and food-safety standards, and run for up to 100,000 hours of continuous uptime.

Aurora Flight Sciences, a Boeing company, uses a UR3 arm as part of its Robotic Copilot concept. The goal is “to create a portable and extensible hardware and software toolbox introducing of new levels of automation across a wide variety of military and civilian aircraft that ultimately reduce crew requirements.” The Aircrew Labor In-Cockpit Automation System, or ALIAS, would combine sensors, a tablet interface for pilots, and flight-control and mission software. The cobot enables it to interact with cockpit controls designed for human pilots.
People have more trust in robots than their managers, according to the second annual AI at Work study conducted by Oracle and Future Workplace, a research firm preparing leaders for disruptions in recruiting, development and employee engagement. The study of 8,370 employees, managers and HR leaders across 10 countries, found that AI has changed the relationship between people and technology at work and is reshaping the role HR teams and managers need to play in attracting, retaining and developing talent.

But a new survey shows some workers have much friendlier views toward AI. Oracle and Future Workplace found 82% of workers believe robot managers are better at certain tasks – such as maintaining work schedules and providing unbiased information – than their human counterparts.

And almost two-thirds (64%) of workers worldwide say they would trust a robot more than their human manager. In China and India, that figure rises to almost 90%.

Workers in India (89 percent) and China (88 percent) are more trusting of robots over their managers, followed by Singapore (83 percent), Brazil (78%), Japan (76 percent), UAE (74 percent), Australia/New Zealand (58 percent), U.S. (57 percent), UK (54 percent) and France (56 percent).

When asked what robots can do better than their managers, survey respondents said robots are better at providing unbiased information (26 percent), maintaining work schedules (34 percent), problem solving (29 percent) and managing a budget (26 percent).

When asked what managers can do better than robots, workers said the top three tasks were understanding their feelings (45 percent), coaching them (33 percent) and creating a work culture (29 percent).
Self-driving cars combine a variety of sensors to perceive their surroundings, such as radar, lidar, sonar, GPS, odometry and inertial measurement units.

Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage

A self-driving car, also known as an autonomous vehicle (AV), connected and autonomous vehicle (CAV), driverless car, robo-car, or robotic car, is a vehicle that is capable of sensing its environment and moving safely with little or no human input.

Waymo, the company that arose from the self-driving car project by Google, no longer has a monopoly on this industry. Instead, every significant automobile producer is pursuing this technology, with Uber being one of the strongest players. The users of this service can now get matched with a self-driving Uber when they request the service, so they can get a glimpse of the future.
We’re looking into a different future for healthcare, too. Instead of visiting a primary care physician who will give us a check-up with a simple stethoscope, we’ll have intelligent robots performing these tasks. They will interact with patients, check on their conditions, and evaluate the need for further appointments.
Pharmabotics will bring more huge changes. They'll be like ATMs for medicines, so we can get the medications we need while avoiding the inconvenience of talking to a stranger about our health issues.
The size related challenge is the ability to measure, manipulate, and assemble matter with features on the scale of 1 to 100 nm.

So far the nanorobotics community was able to
Develop large-scale manipulators with nanoscale precision and manipulation capability called nanomanipulators.
Demonstrate experimentally the development of several nanocomponents such as various types of nanostructures, nanosensors, nanomotors, nanocomputers, etc. that eventually could be used in the assembly of nanorobots.
Develop and test successfully simple nanorobots based on molecular machines and nanoparticles

Applications of NanoRobots:
In surgery.
Detection of toxic cells.
Ability to enter cells and correct DNA or a deficiency.
Repair cells, tissue, and even organs.
Break up blood clots or even kidney stones.
Treatment of cancer.
Diabetes- Monitoring glucose level
5G patrol robot developed by the Guangzhou Gosunch Robot Company: Whenever an abnormal or suspicious events such as absence of facial mask or high body temperature is detected by the robot, a alert is send to the relevant authorities to take necessary initiatives to handle the event

Doctors and nurses of a hospital in Italy takes help of a robot nurse named Tommy to monitor different vital sings from devices of patient's room. Tommy also allows patients to communicate with the doctors by sending messages.

Portable disinfection robots use ultraviolet-C (UV-C) light or hydrogen peroxide vapor (HPV) to disinfect. The robots scan the environment using LiDAR technology. It relies on Simultaneous Localization and Mapping (SLAM) to navigate and operate completely autonomously. When people are around, its sensors detect motion and shut the UV lights automatically.
Shanghai-based Keenon Robotics launched a “smart solutions for the epidemic areas” plan, sending hundreds of delivery robots to nearly 100 hospitals in the aected areas across China. Peanut model robots from Keenon Robotics are equipped with Astra Mini S cameras, LIDAR, infrared, and ultrasonic sensors. The robot navigates via a predefined route or using simultaneous location and mapping routines.

San Francisco based medical product delivery company Zipline drone is delivering vaccines, medicines, and personal protective equipment. If an elderly or at-risk individual needs their medication, Zipline drone can help them receive it without an in-person
visit. The drone delivery is possible within 22500 km2 area and it can y at 100 km/h speed. The pay load of the drone is 1.8 kg.
When designing the next generation of logistics robots, there is one key element needed to tie together advanced perception, mobility, and collaboration: computational
power, also known as ‘Brains’.
GPUs are often more than 10x faster at repetitive tasks than more general-purpose and well-known central processing units (CPUs). By using multiple GPUs in parallel, engineers can increase speeds yet again.
Researchers in the Robot Learning Lab at Cornell University developed a robot that can prepare a cup of latte without ever having seen the machine before – the robot does this by visually observing the machine and by reading online instruction manuals, similar to how humans learn.
Physics toolbox android
AutoCAD - Preferred for 2D design of robot
SolidWorks - Preferred for 3D design of robot

Simulation
RoboDK- Used to simulate industrial robot
Webot- Used mostly to simulate robot in complicated real world environment
Gazebo: Used to design robot and train AI system.
Please leave humanoid robot (so called!), LFR

Artificial Intelligence:
Reinforcement Learning: Is used to teach robot to take action that maximizes future possible reward.
Particle Swarm Optimization: Used for swarm optimization.
Ant Colony Optimization: Used for swarm optimization

Motion Planning:
Dijkstra’s Algorithm: Single Source Shortest Path Algorithm.
Floyd Warshall Algorithm: All Pair Shortest Path Algorithm.

Robot localization is the process of determining where a mobile robot is located with respect to its environment. Localization is one of the most fundamental competencies required by an autonomous robot as the knowledge of the robot's own location is an essential precursor to making decisions about future actions. In a typical robot localization scenario, a map of the environment is available and the robot is equipped with sensors that observe the environment as well as monitor its own motion. The localization problem then becomes one of estimating the robot position and orientation within the map using information gathered from these sensors.

Motion planning, also path planning (also known as the navigation problem or the piano mover's problem) is computational problem to find a sequence of valid configurations that moves the object from the source to destination. The term is used in computational geometry, computer animation, robotics and computer games.
For example, consider navigating a mobile robot inside a building to a distant waypoint. It should execute this task while avoiding walls and not falling down stairs. A motion planning algorithm would take a description of these tasks as input, and produce the speed and turning commands sent to the robot's wheels. Motion planning algorithms might address robots with a larger number of joints (e.g., industrial manipulators), more complex tasks (e.g. manipulation of objects), different constraints (e.g., a car that can only drive forward), and uncertainty (e.g. imperfect models of the environment or robot).

Robot navigation means the robot's ability to determine its own position in its frame of reference and then to plan a path towards some goal location. In order to navigate in its environment, the robot or any other mobility device requires representation, i.e. a map of the environment and the ability to interpret that representation.
Navigation can be defined as the combination of the three fundamental competences:
Self-localisation
Path planning
Map-building and map interpretation
Some robot navigation systems use simultaneous localization and mapping to generate 3D reconstructions of their surroundings.

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