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NUS CS5247 Real-Time Combinatorial Tracking of a Target Moving Unpredictably Among Obstacles Hector H. Gonzales-Banos, Cheng-Yu Lee and Jean-Claude Latombe.

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Presentation on theme: "NUS CS5247 Real-Time Combinatorial Tracking of a Target Moving Unpredictably Among Obstacles Hector H. Gonzales-Banos, Cheng-Yu Lee and Jean-Claude Latombe."— Presentation transcript:

1 NUS CS5247 Real-Time Combinatorial Tracking of a Target Moving Unpredictably Among Obstacles Hector H. Gonzales-Banos, Cheng-Yu Lee and Jean-Claude Latombe Presented By: Amit Jain

2 NUS CS52472 Outline Introduction Problem Statement Approach Evaluation Future Work Conclusion

3 NUS CS52473 Introduction Consider a scenario involving... Team of autonomous robots Performing independent tasks At a remote location Requirements for ideal debugger: Dynamic Environment Unmapped Territory

4 NUS CS52474 Problem Statement Maximize Escape Time Unknown Environment Nondeterministically uncertain target

5 NUS CS52475 Approach Acts = {} For each EscapePath ep SEP Acts = Acts maximizeEscapeTime(ep) BestAction = combine(Acts)

6 NUS CS52476 Approach: maximizeEscapeTime Basic Approach Maximize escape time Pros Directly addresses the problem Cons Computationally expensive to calculate Alternatives/Proxies Shortest Distance to Escape as proxy Risk Function as proxy

7 NUS CS52477 Approach: SDE Maximize Shortest Distance to Escape Pros Correct in holonomic case Related in non-holonomic case Cons Non-linear Relationship

8 NUS CS52478 Approach: Risk Function Minimize risk Pros: Polynomial relationship with SDE Considers pursuer's position

9 NUS CS52479 Approach Acts = {} For each EscapePath ep SEP Acts = Acts maximizeEscapeTime(ep) BestAction = combine(Acts)

10 NUS CS Approach: Combining Actions Naive Approach: Average over actions Pros: Easy to Implement Intuitive Cons: Over Representation of Escape Paths Alternative Approach: Average over EPTs

11 NUS CS Evaluation Influence of escape paths on risk Transient response of target tracker Tracking over long time

12 NUS CS Future Work Extending to 3-D Learning the map

13 NUS CS Conclusion Reactive target follower Novelties: Linear time calculation of escape path New proxy for escape time Avoids localization issues

14 NUS CS524714

15 NUS CS524715


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