1. 1 Toward Autonomous Free-Climbing Robots Tim Bretl Jean-Claude Latombe Stephen Rock Special thanks to Eric Baumgartner, Brett Kennedy, and Hrand Aghazarian at the Planetary Robotics Lab, NASA-JPL

2. 2 Goal Develop integrated control, planning, and sensing capabilities to enable a wide class of multi-limbed robots to climb steep natural terrain.

3. 3 LEMUR IIb, Planetary Robotics Lab, NASA-JPL Generic vs. Specific Robot Generic Specific Sitti and Fearing, UC Berkeley

4. 4 Previous Multi-Limbed Climbing Robots Each exploits a specific surface property NINJA II Hirose et al, 1991 Neubauer, 1994 Yim, PARC, 2002

5. 5 Free Rock Climbing is about Natural Friction …

6. 6 … and Non-Gaited Motion Gaited Non-Gaited

7. 7 Overall, rock climbing is about how to apply strength, not about strength itself it is a problem-solving activity

8. 8 Example System

9. 9 Equilibrium Constraint Feasible positions of robot’s center of mass

10. 10 Configuration Space For each combination of knee bends: –Position (x P,y P ) of pelvis –Joint angles (  1,  2 ) of free limb

11. 11 Feasible Space 11 22   

12. 12 1.Simple test for the feasibility of (x p,y p ) where… Feasible Space

13. 13 1.Simple test for the feasibility of (x p,y p ) 2.Feasible (  1,  2 ) varying with (x p,y p ), in one half of  f where… ff Feasible Space

14. 14 1.Simple test for the feasibility of (x p,y p ) 2.Feasible (  1,  2 ), varying with (x p,y p ), in one half of  f 3.Switching between halves of  f Feasible Space

15. 15 Motion Planning Basic Approach (Probabilistic Roadmap) –Sample 4D configuration space –Check equilibrium condition –Check (self-)collision –Check torque limit Refined approach –Sample 2D pelvis space, lift to full 4D paths –Narrow passages are found in the 4D space

16. 16 1.Achieve  2 =0 2.Move with  2 =0 3.Switch between halves of  f 4.Move with  2 =0 5.Move to goal

17. 17 backstep highsteplieback

18. 18 JPL’s LEMUR robot

19. 19

20. 20 Current Work  Terrain sensing and hold detection  Force control and slippage sensing  Uncertainty (hold location, limb positioning)  Motion optimization  Extension of feasible space analysis

21. 21 What’s Next? Xtreme ironing

22. 22 Xtreme ironing is one of the fastest-growing sports in the world

23. 23