1. Laboratory for Perceptual Robotics – Department of Computer Science Whole-Body Collision-Free Motion Planning Brendan Burns Laboratory for Perceptual Robotics University of Massachusetts Amherst

2. 2 Laboratory for Perceptual Robotics – Department of Computer Science Why motion planning? The real world is complicated Collisions are hazardous Mobility

3. 3 Laboratory for Perceptual Robotics – Department of Computer Science How to motion plan?  Configuration space is big! (exponential)  Exact methods are intractable  Sampling-Based Planning (PRM)

4. 4 Laboratory for Perceptual Robotics – Department of Computer Science Probabilistic Roadmap Planning Kavraki & Overmars 1996 ?

5. 5 Laboratory for Perceptual Robotics – Department of Computer Science 1 2 3 6 7 8 9 5 4 10 6 38 9 42 [1..5][7..10] [1..2] [4..5] [9..10]

6. 6 Laboratory for Perceptual Robotics – Department of Computer Science Structure & Exploration  Identify the structure to expect  Acquire knowledge about structure  Exploit understanding as a guide

7. 7 Laboratory for Perceptual Robotics – Department of Computer Science Models

8. 8 Laboratory for Perceptual Robotics – Department of Computer Science Predictive Models

9. 9 Laboratory for Perceptual Robotics – Department of Computer Science Active Sampling

10. 10 Laboratory for Perceptual Robotics – Department of Computer Science Predictive Edge Checking  Edge checking is expensive  Our predictive model already exists  Construct a predictive roadmap

11. 11 Laboratory for Perceptual Robotics – Department of Computer Science Predictive Roadmaps

12. 12 Laboratory for Perceptual Robotics – Department of Computer Science Path Extraction

13. 13 Laboratory for Perceptual Robotics – Department of Computer Science Path Extraction

14. 14 Laboratory for Perceptual Robotics – Department of Computer Science Path Extraction

15. 15 Laboratory for Perceptual Robotics – Department of Computer Science Path Extraction

16. 16 Laboratory for Perceptual Robotics – Department of Computer Science Path Extraction

17. 17 Laboratory for Perceptual Robotics – Department of Computer Science Experiments

18. 18 Laboratory for Perceptual Robotics – Department of Computer Science 9-DOF

19. 19 Laboratory for Perceptual Robotics – Department of Computer Science 12-DOF

20. 20 Laboratory for Perceptual Robotics – Department of Computer Science Coming Soon…

21. 21 Laboratory for Perceptual Robotics – Department of Computer Science Stop

22. 22 Laboratory for Perceptual Robotics – Department of Computer Science Models

23. 23 Laboratory for Perceptual Robotics – Department of Computer Science Optimal Sampling

24. 24 Laboratory for Perceptual Robotics – Department of Computer Science Optimal Sampling ?

25. 25 Laboratory for Perceptual Robotics – Department of Computer Science Active Sampling

26. 26 Laboratory for Perceptual Robotics – Department of Computer Science Models  An approximate model of our current understanding  Predicts the state of unobserved configuration- space  Locally Weighted Regression (Atkeson et al.)  Others are possible

27. 27 Laboratory for Perceptual Robotics – Department of Computer Science Active Sampling  Our current understanding suggests areas of improvement  Sample to reduce maximize the expected reduction in model variance (Cohn et al.)  Direct sampling in proportion to complexity