1. Autonomous Navigation of a
Humanoid Robot over Unknown Rough Terrain using a Laser Range Sensor
Koichi Nishiwaki, Joel Chestnutt, Satoshi Kagami
The International Journal of Robotics Research. 17 August 2012.

2. Bipedal Robots HRP-2 38-DOF
Good - Terrain with obstacles, discontinuous height changes, roughness
Challenging Problem - Naturally unstable
HRP-2
38-DOF

3. Proposed Solution Advanced System
no need for assumptions or previous knowledge of objects in environment
ability to step on inclined terrain
Advanced System
Laser-based Perception System
Footstep Planner
Robust Walking Controller
Operational Interface - assign commands / goal positions

4. Autonomous Navigation System

5. Laser-based Perception System
Scanning-type laser range sensor with a swinging mechanism
Terrain map for footstep planning - grid of 0.02m x 0.02m cells with height value
Measurements from up to 30m
Convert distance data from single sweep into absolute 3D positions using position of robot and angle of sensor

6. Terrain shape measurement of a flat office floor
Observed cells

7. Error increases with distance from sensor

8. Terrain with regions of different heights and a wall
Calculated heights of cells

9. Improved method to Reduce Noise
if standard dev < 0.01:
average heights
else:
sort height large to small
calc std dev top n
repeat, n+1, while std dev < 0.01
take average of top n

10. Footstep Planning example transition set
A* search to generate sequence of footstep locations for reaching given goal state
Limit landing positions of swing foot relative to stance foot to a finite number Cost associated with each possible footstep: terrain height, inclination, roughness (Chestnutt 2003) Trajectories planned after footstep chosen “Guide curve” used as the A* heuristic – planning “ahead” guidance
Adaptive Action Model
example transition set

11. Dynamically Stable Trajectory Generation
generate walking trajectories that start from estimate actual motion
takes time – approx. 36ms per step
estimate initial conditions

12. Sensor Feedback Control System
execute specified torso motion, even if terrain shape is different than expected
repetitive trajectory generation compensates for divergence
ground reaction force control: let feet handle the uneven terrain
desired reaction force and velocity in response to environment
Keeps torso motion insensitive to difference of terrain shape

13. Estimating Absolute Posture
positions and velocities of the torso and feet
inertial measurement unit (IMU) - gyroscopes, servo accelerometers
rotate robot around measured ZMP

14. Operational Interface Graphical user interface

15. Mixed-reality interface

16. Joystick interface

17. Navigation Experiments

18. Evaluation of measurement accuracy for height and inclination

19. Videos

20. Conclusion
Achieved autonomous navigation of humanoid robot on unknown rough terrains
no use of assumptions or previous knowledge of the shapes of objects in the environment Different modes of operation: GUI, HMD, Joystick