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

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

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

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

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

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

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

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 , 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. 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 , Jul
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. Background
[3] Chow, Clark, Huissoon, Assigning Closely Spaced Targest to Multiple Autonomous Underwater Vehicles, Journal of Ocean Engineering, Vol
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. Background
[3] Chow, Clark, Huissoon, Assigning Closely Spaced Targest to Multiple Autonomous Underwater Vehicles, Journal of Ocean Engineering, Vol
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. Proposed Solution N Task Point Locations Task Assignment Algorithm
Task Sequence
Algorithm
AUV Path Construction
Algorithm
M Task
Assignments
M Task
Sequences
M AUV
Paths
M AUV Locations

14. Proposed Solution Task Assignment Algorithm Task Sequence 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. 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. Milestones Data Task Jan 15 Develop multi-AUV simulator Feb 1
Implement Auction Based Task Planner MTSP solution
Mar 1
Mar 8
Run 100 simulations for each parameter setting
Mar 15
Present planner and results