1. 1 E190Q – Project Introduction Autonomous Robot Navigation Team Member 1 Name Team Member 2 Name

2. 2 Preliminary Project Presentation 1.Problem Definition  Written definition  Overview image  Provide performance metrics 2.Background  Include 3+ references  Be sure to provide full citation  Use images from references  Describe key findings of paper

3. 3 Preliminary Project Presentation 3.Proposed Solution  Block Diagram including sensors and actuators (inputs, outputs, closed loop ) 4.Measurable Outcomes  List potential plots or tables of performance metrics 5.Milestones  List major tasks with dates  Identify team member responsible if applicable

4. 4 Preliminary Project Presentation  Notes:  5 minute time limit for slides  Both students must present  Students will help with assessment  Presentations on Monday, April 1, 2013

5. 5 Problem Definition  To design a Multi AUV Task Planner that considers kinematic constraints

6. 6 Problem Definition  To design a Multi AUV Task Planner that considers kinematic constraints

7. 7 Problem Definition  Given  N task point locations and M AUVs  Determine  The assignment of tasks to AUVs and AUV tours of assigned task points that minimizes the maximum path length all AUV tours.

8. 8 Problem Definition  Performance Metrics  Maximum AUV tour length  Planning Time or run time complexity

9. 9 Background  [1] R. Zlot, A. Stentz, M. B. Dias, and S. Thayer, Multi-robot exploration controlled by a market economy, in Proc. IEEE Conf. Robotics and Automation, vol.3, Washington, DC, pp. 3016-3023, 2002.  Used an auction based method in which task points are auctioned off to robot with the highest bid (i.e. lowest additional path cost).  Decentralized.  Fast, O(MN), but Sub-optimal

10. 10 Background  [2] L. E. Dubins, On curves of minimum length with a constraint on average curvature and with prescribed initial and terminal position and tangents, American J. Mathematics, vol. 79, no. 3, pp. 497-516, Jul. 1957.  Demonstrated the shortest path between points when minimum turn radius is a constraint  Shortest Path is a connected curve of minimum radius, straight line segment, and curve of minimum radius

11. 11 Background  [3] Chow, Clark, Huissoon, Assigning Closely Spaced Targest to Multiple Autonomous Underwater Vehicles, Journal of Ocean Engineering, Vol. 41-2 2007.  Algorithm considers vehicle dynamics and currents  Demonstrated that using euclidean distance between task points is a poor metric for calculating tour path length when task points are tightly spaced  Real Ocean Deployments

12. 12 Background  [3] Chow, Clark, Huissoon, Assigning Closely Spaced Targest to Multiple Autonomous Underwater Vehicles, Journal of Ocean Engineering, Vol. 41-2 2007.  Algorithm considers vehicle dynamics and currents  Demonstrated that using euclidean distance between task points is a poor metric for calculating tour path length when task points are tightly spaced  Real Ocean Deployments

13. 13 Proposed Solution N Task Point Locations M AUV Locations Task Assignment Algorithm Task Sequence Algorithm AUV Path Construction Algorithm M AUV Paths M Task Assignments M Task Sequences

14. 14 Proposed Solution  Task Assignment Algorithm  Cluster N points into M groups K-means clustering algorithm  Assign one AUV to each cluster using a greedy assignment algorithm  Task Sequence Algorithm  Find next closest point algorithm  AUV Path Construction Algorithm  Fit arc path segments between each task point of a sequence

15. 15 Measurable Outcomes  Run time as a function of the number of robots  Average AUV path length for various ratios of N/M  Comparison of average AUV path length when using standard MTSP planner and MTSP planner that considers kinematic constraints

16. 16 Milestones DataTask Jan 15Develop multi-AUV simulator Feb 1Implement Auction Based Task Planner MTSP solution Mar 1Implement Auction Based Task Planner MTSP solution Mar 8Run 100 simulations for each parameter setting Mar 15Present planner and results