DEVIEW2015 DAY1. DRC hubo technical review - 이정호님

1. DRC-HUBO:
Technical Review
Jungho Lee Ph.D
Rainbow Robotics, CEO

2. contents
1. Robot Platform: HUBO
2. Real-time OS & Framework
3. Control Strategy
4. DRC Finals

3. 1.
Robot Platform
HUBO

4. 1.0 Rainbow
Best Engineering
&Technology
university in Korea
World: 17th(QS), 26th(THE)
Best Robotics Research
Center in Korea

5. 1.1 Hardware Overview
History of humanoid robot, HUBO

6. 1.1 Hardware Overview
DRC-HUBO
• Height : 155cm
• Weight : 60kg
(2013)
DRC-HUBO+
• Height : 175cm
• Weight : 80kg
(2015)
IMU sensor
LIDAR
Computer
Battery
Foot
Hand
P.A.C. sys.
Wheel

7. 1.1 Hardware Overview

8. 1.2 Light and Rigid Design
• Exoskeletal structure
• Avoid cantilever
• No external cables
• Modular design
- Torso -
- Leg -
- Arm -

9. 1.2 Light and Rigid Design
• No external cables
- There is no external cables by using
hallow shaft
- Protect cables from malfunction and
external impact
• Modular design
- Facilitate assembly and repair process

10. 1.3 Effective Heat Dissipation System
• Specially designed cooling
fins with fans
- Knee joint and Hip pitch joint need
much heat dissipation
- Specially designed fins absorb heat
from motors and motor control
boards
• Heat dissipation by using
contact with frame
- Heat dissipation from motors and
motor control boards to aluminum
body frame

11. 1.4 Transformable Humanoid

12. 1.5 Robust Motor Driver
2ch and 1ch motor controllers

13. 1.6 Smart Power Management
Super Capacitor
LCD Monitor
Main Controller
Li-Ion
Battery 48V / 11.4 Ah

14. 1.7 Reliable Internal Communication
PC
CAN
(2ch)
isolator isolator isolator isolator
FT sensorJoint Motor
Controller
Joint Motor
Controller
Can High
Can Low
CAN
(2ch)
(USB Connection)
Right Leg Left Leg Right Arm Left Arm

15. 1.8 Reliable Vision/LIDAR System
PL
PM
PC
HUBO head, rotating vision sensor system HUBO head calibration
Due to rotating vision sensor system, we can obtain full 3D point cloud of target
area and control laser sparsity using motor sweeping speed

16. 2.
Real-time OS &
Framework
PODO-RT

17. 2.1 How to move robots?
PODO Framework?
1. “PODO” is named from Korean word “포도”, grape in English.
2. We call each process in PODO as “AL”(알), grape berry in English.
3. Many programs(processes) for controlling robots are attached to shared memory.

18. 2.2 PODO Framework
Module 1
Library
Module 2
Library
Module n
Library
Dependent Structure Multi-agent system

19. 2.2 PODO Framework
Module 1
Process
Module 2
Process
Module n
Process
Independent Structure Multi-agent system
PODO

20. 2.2 PODO Framework

21. 2.3 Real-time OS
• “A system is said to be real-time if the correctness of a computation depends not only on the logical
correctness but also on the time at which the results are produced [1].”
[1] Shin, Kang G., and Parameswaran Ramanathan. "Real-time computing: A new discipline of computer science and engineering." Proceedings of the IEEE 82.1 (1994):
6-24.
Data
Validity
1
Time
deadline
Time
Data
Validity
1
deadline
System
Unstability
Time
deadline system failure
System
Unstability
Time
deadline degrade
system quality
Hard real-time
Soft real-time
missing a deadline is a total system
failure.
the usefulness of a result degrades
after its deadline, thereby
degrading the system's quality of
service.

22. 2.3 Real-time OS

23. 2.3 Real-time OS
l Firmware
• 시스템이 간단함
• Hard real-time
• 실시간 연산속도에 제한 받음
• 기능이 제한적임 (비 OS)
• UI가 제한적임
Hard Real-time
Robot System
Firmware based
Embedded System
l GPOS(Soft RTOS)
• GPOS의 기능을 활용할 수 있음
• PC선택에 비 제한적임
• Soft real-time 혹은 hard real-time
이지만 선택적 명령 수행으로 제한됨
• 실시간 연산속도에 제한 받음
Hard Real-time
Robot System
General Purpose
OS(Robot framework)
Firmware based
Embedded System
Non/Soft Real-time
Communication
Hard Real-time
Robot System
General Purpose
OS(Robot framework)
Communication
Hard RTOS
• Hard real-time
• GPOS의 기능을 활용할 수 있음
• 복잡한 연산도 가능
• 비싼 가격
• 시스템의 구성이 어려움
• RTOS에 따라 PC가 제한적임
• RTOS에 상응하는 GPOS를 쓸 수밖에 없음
• Real-time 통신 모듈을 직접 구현해야 함
l Hard RTOS

24. 2.4 PODO-RT
All the actions must start and end within one cycle of control period.
The updating time of sensor and the sending time of reference should be regular and periodic.
Time Offset
(read sensor)
Time Offset
(send reference)
Calculate
Reference
(with sensor)
Sensor #1
Sensor #N
Joint #1
Joint #2
Joint #N
Robot
Hardware
Control Period
(n+1)
(n)
(n-1)
(n)
(n+1)
(n-1)
(n)
(n+1)
(n-1)
(n+1)
(n-1)
(n)
(n-1)
(n)
(n+1)
Send Reference to Robot
Pass Reference to
Daemon
Request Reference
Control
Period
(5ms)
ALDaemon
Working
Time
Suspend Time
Robot
Request Sensor Data
Generate Next Reference
(Use Sensor Data)
Synchronize Reference &
Sensor Data

25. 2.4 PODO-RT
PODO ALs
Shared Memory
PODO-RT
Communication
(EtherCAT, CAN, RS485, etc..)
Robot System
(Controllers, sensors, etc..)
General Purpose OS
(OSX, Linux, Window, etc..)
Robot
Framework
PODO DaemonReal-time Kernel

26. 3.
Control Strategy

27. 3.1 Supervisory and Autonomy
> Supervisory : Where to go and direction
Case - Movement

28. 3.1 Supervisory and Autonomy
> Supervisory : Set Valve ROI range
Case - Task

29. 3.1 Supervisory and Autonomy
Drill recognition Valve recognition Terrain recognition
Vision recognition result

30. 3.1 Supervisory and Autonomy
Rotate drill to grab in correct orientation Try Several different Position and orientation to turn
on the Drill
Use Mic to Detect Drill status
<Autonomy in motion : Drill task>

31. 3.1 Supervisory and Autonomy
<Autonomy in motion : Manual operation>
Auto redundancy adjust in manual control

32. 3.1 Supervisory and Autonomy

33. 3.2 Whole System Configuration
Robot-Motion
Ubuntu 12.04 + Xenomai
i5-4250U 1.30GHz x 4
Vision-Grabbing
Windows 8.1
i5-4250U 1.30GHz x 4
Vision-Field
Windows 8.1
Xeon E5-1620 3.70GHz x 8
Motion-Field
Ubuntu 14.04
i7-4790K 4.00GHz x 8
OCS-Main
Ubuntu 14.04
i7-4790 3.60GHz x 8
OCS-Virtual
Ubuntu 14.04
i7-4790 3.60GHz x 8
OCS-Monitoring
Ubuntu 14.04
I7-4700MQ 2.40GHz x 8
TCP
TCP Server
UDP
CAN Bus
Robot Field
OCS
Motor
Controller #1
Motor
Controller #2
Motor
Controller #N
Sensor #1
Sensor #2
Sensor #N
LIDAR
Camera #1
Camera #2
DRC-HUBO+

34. 3.3 Degraded Comm. Handling

35. 3.4 Intuitive User Interface
Monitor#1
Monitor#2
Joint Status
Program Status
Image view
Sensor info.
3D view
User button
Error signal
Z-map

36. 3.5 Compliance Control
Difficulties of force control
- System is originally highly geared actuator
- Harmonic drive has less back-drivability
- When motor drivers on(FET ON), motor
experience braking effect
- Non complementary switching mode
-> Cancel braking effect
- Friction compensation
-> Make back-drivable

37. 3.5 Compliance Control

38. 3.6 Mobility
Robot
Force,
Moment,
ZMP,
Angle,
Velocity,
Vision,
Etc.
Walking
Motion
Planner
Foot Position
Foot Pose
Pelvis Height
Pelvis Pose
Walking
Pattern
Generator
CoM Whole Body
Inverse
Kinematics
Walking Pattern
Controller
Predictive Motion
Controller
Real-Time
Balance
Controller
Joint
Angle
l Walking Framework

39. 3.6 Mobility
l Balance Control
High precision rate gyro
• Fiber Optics Gyro(FOG)
• Superior bias instability
(≤0.1°/hr, 1σ)

40. 3.6 Mobility
StableC
Coliision freeC
allowable joint rangeC
l Walking Motion Planner
Valid Plane Extraction
Collision
Joint Limit
Generate Candidate
Configuration
LIDAR DATA
Motion
Checker
Priority Based
Parameter
Modification
1. Hip Height
2. Hip Rotation
3. Toe-off Motion
4. Foot Orientation
5. Foot Position
Optimized Walking
Configuration
Yes
No
Search the space of stable
configuration

41. 3.6 Mobility
• Hip Height
Modification
Motion
• Toe Off and Pelvis
Rotation Motion
l Extending walking stride

42. 3.6 Mobility

43. 3.6 Mobility

44. 4.
DRC Finals

45. 4.1 Tasks
Driving
Egress
Door
Valve
Drill
Surprise
Stair
Debris
Terrain

46. 4.2 Driving Task

47. 4.3 Egress Task

48. 4.4 Door Task

49. 4.5 Valve Task

50. 4.6 Drill Task

51. 4.7 Unknown Task

52. 4.8 Terrain Task

53. 4.9 Debris Task

54. 4.10 Stair Task

55. 4.11 DRC Finals: TeamKAIST

56. 4.11 DRC Finals: TeamKAIST
Prof. Junho OhDr. Jungho Lee
Dr. Inhyeok Kim
Dr. Jungwoo Heo

57. 4.12 We have to do more and more…

58. Q&A

59. Thank You