E190Q – Project Introduction Autonomous Robot Navigation Team Member 1 Name Team Member 2 Name 1 Preliminary Project Presentation 1. Problem Definition Written definition Overview image Provide performance metrics 2. Background 2 Include 3+ references Be sure to provide full citation Use images from references Describe key findings of paper 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 3 List major tasks with dates Identify team member responsible if applicable Preliminary Project Presentation Notes: 4 5 minute time limit for slides Both students must present Students will help with assessment Presentations on Monday, April 1, 2013 Problem Definition To design a Multi AUV Task Planner that considers kinematic constraints 5 Problem Definition To design a Multi AUV Task Planner that considers kinematic constraints 6 Problem Definition Given N task point locations and M AUVs Determine 7 The assignment of tasks to AUVs and AUV tours of assigned task points that minimizes the maximum path length all AUV tours. Problem Definition Performance Metrics 8 Maximum AUV tour length Planning Time or run time complexity 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 9 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 10 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 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 Proposed Solution N Task Point Locations M AUV Locations 13 Task Assignment Algorithm M Task Assignments Task Sequence Algorithm M Task Sequences AUV Path Construction Algorithm M AUV Paths 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 14 Fit arc path segments between each task point of a sequence 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 15 Milestones Data 16 Task Jan 15 Develop multi-AUV simulator Feb 1 Implement Auction Based Task Planner MTSP solution Mar 1 Implement Auction Based Task Planner MTSP solution Mar 8 Run 100 simulations for each parameter setting Mar 15 Present planner and results