1. Legged Locomotion Planning Kang Zhao B659 Intelligent Robotics Spring 2013 1

2. Planning Biped Navigation Strategies in Complex Environments Joel Chestnutt, James Kuffner, Koichi Nishiwaki, Satoshi Kagami Planning Biped Navigation Strategies in Complex Environments Joel Chestnutt, James Kuffner, Koichi Nishiwaki, Satoshi Kagami 2

3. O Global terrain map M O Goal O Primitive set {Trans} O Search algorithm 3

4. Algorithm - Biped Robot Model 4

5. Algorithm- State transitions 0 1 2 3 4 56 7 A 16-transitions set 5

6. Algorithm- Environment 6

7. Algorithm- State Evaluation Location metric to evaluate a location’s cost Slope angle Roughness Stability Largest bump Safety 7

8. Slope angle Roughness Stability Largest bump Safety 8 The slope angle of the surface at the candidate location. Perfectly horizontal surfaces are desired. The slope angle is computed by fitting a plane h(x, y) to the cells in the location. It’s purpose is to take into account the possible inaccuracy of foot positioning. This can be computed using the roughness and largest bump metrics, using the cells around the foot location

9. Algorithm- State Evaluation Step metric to evaluate cost of taking a step Cost of transition Penalty for height change Collision check 9

10. Algorithm- State Evaluation Euclidean distance Relative angle Height difference 10

11. Best First Search 11

12. A* Search 12

13. Search tree Searching the State Space A schematic view

14. Search tree Searching the State Space A schematic view

15. Search tree Searching the State Space A schematic view

16. Search tree Searching the State Space A schematic view

17. Search tree Searching the State Space A schematic view

18. Search tree Searching the State Space A schematic view

19. Results O Cluttered terrain 19

20. Results O Multi-level terrain 20

21. Results O Uneven ground with obstacles 21

22. Comparisons O Distance to goal O Transitions and obstacle effects O Metric weights 22

23. A 26-transitions set A 40-transitions set BFS 23

24. 24 Performance comparison of A* and BFS for increasing numbers of stairs along the path

25. 25

26. 26

27. 27 Local-minimum problem

28. 28 Online Experiments Stereo vision system Planner Footstep sequence Trajectory generator Walking area map

29. Following work O A tired planning Strategy for biped navigation, 2004 O Biped navigation in rough environments using on-board sensing, 2009 29

30. Multi-Step Motion Planning for Free- climbing Robots Tim Bretl, Sanjay Lall, Jean-Claude Latombe, Stephen Rock Multi-Step Motion Planning for Free- climbing Robots Tim Bretl, Sanjay Lall, Jean-Claude Latombe, Stephen Rock 30