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Toward Autonomous Free- Climbing Robots

Toward Autonomous Free- Climbing Robots

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Toward Autonomous Free- Climbing Robots

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  1. Toward Autonomous Free-Climbing Robots Tim Bretl, Jean-Claude Latombe, and Stephen Rock May 2003 Presented by Randall Schuh

  2. Motivation • Non-specific autonomous rock-climbing robots could benefit several applications: • Search-and-rescue • mountainous terrain • broken urban environments • Exploration • Sub-surface environments • Planetary, especially on Mars • New modes of motion for humanoid robots

  3. Previous Work • Climbing robots • exploit unnatural surface properties, e.g.: • Peg into hole • Suction pads (grass, steel surfaces) • Track and legged robots • ascend slopes up to 50 degrees • Few works consider choosing foot placement • Grasping • usually emphasizes force-closure

  4. Planar Model • 3 identical limbs, 8 dof • Ignores self-collision • Coulomb friction • Motion occurs in 4-D subspace of C-space

  5. Planar Motion Planning • One-Step-Climbing Problem • Geometrical insight allows solution path planning in 2 dimensions (pelvis position) • Uses PRM techniques • Instead of collisions, the planner tests for equilibrium • Uses dynamic testing algorithm (Class 3) • Uses a simple smoothing technique

  6. Coulomb friction cones Ffriction ≤ μ N Ffriction ≤ μ F cos θ Stable if: F sin θ < μ F cos θ Friction cone: tan φ ≤ μ φ ≤ tan–1μ

  7. + = – + = 0 E Dependent on x Dependent only on x Equilibrium Region

  8. Geometrical Analysis • Free space of the free limb consists of 2 connected subsets

  9. Planar Example1

  10. Planar Example2

  11. Planar Example3

  12. Planar Example4

  13. Planar Example5

  14. Planar Example6

  15. Planar Example7

  16. Planar Example8

  17. Climbing up mountain (first 15 sec)

  18. 3D Model – LEMUR1 II • Each limb has a spherical shoulder and a revolute knee (4 dof); limbs are 30 cm long • Joints are mechanically limited • Robot can push or pull from each endpoint • Motion occurs in 13-D subspace of C-space 1Limbed Excursion Mobile Utility Robot – developed by JPL

  19. 3D Motion Planning • Still tests for equilibrium • Uses PQP to test for self-collisions and collisions with environment • Uses a more sophisticated technique for sampling closed kinematic chains • Not yet reduced dimension of problem with geometrical analysis.

  20. 3D Example1

  21. 3D Example2

  22. 3D Example3

  23. 3D Example4

  24. 3D Example5

  25. 3D Example6

  26. 3D Example7

  27. 3D Example8

  28. 3D Example9

  29. Future Work • Apply geometric insight to be able to capture narrow passages more efficiently • Add torque constraints • Implement the algorithm on hardware, which will require • Visual and tactile sensing of grasps • Tactile feedback (slippage detection) • Multi-step planning based on incomplete information

  30. Paper Comparison Common Features: • Planning from a discrete series of grasps • Applying PRM techniques Differences: • Application to real vs. digital environment • Kinematic & equilibrium vs. kinematic constraints