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Toward Autonomous Free-Climbing Robots

This project aims to develop integrated control, planning, and sensing capabilities for multi-limbed robots to climb steep natural terrain. The focus is on generic versus specific robot approaches, with the LEMUR IIb from NASA-JPL being a specific example. The project explores the natural friction and non-gaited motion involved in free rock climbing, treating it as a problem-solving activity. Motion planning techniques are employed to ensure feasibility, equilibrium, collision avoidance, and torque limits. Ongoing work includes terrain sensing, force control, uncertainty management, and motion optimization.

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Toward Autonomous Free-Climbing Robots

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

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

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

  5. Free Rock Climbing is about Natural Friction …

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

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

  8. Example System

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

  10. Configuration Space For each combination of knee bends: • Position (xP,yP) of pelvis • Joint angles (q1,q2) of free limb

  11. p q2 -p q1 p -p Feasible Space

  12. Feasible Space Simple test for the feasibility of (xp,yp) where…

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

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

  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. Achieve q2=0 • Move with q2=0 • Switch between halves of Qf • Move with q2=0 • Move to goal

  17. backstep highstep lieback

  18. JPL’s LEMUR robot

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

  20. What’s Next? Xtreme ironing ? >>> X

  21. Xtreme ironing is one of the fastest-growingsports in the world

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