E190Q – Project Introduction
Autonomous Robot Navigation
Team Member 1 Name
Team Member 2 Name
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Preliminary Project Presentation
1. Problem Definition
 Written definition
 Overview image
 Provide performance metrics
2. Background
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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
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 List major tasks with dates
 Identify team member responsible if
applicable
Preliminary Project Presentation
 Notes:
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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
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Problem Definition
 To design a Multi AUV Task
Planner that considers kinematic
constraints
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Problem Definition
 Given
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N task point locations and M AUVs
 Determine
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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
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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
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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
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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
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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
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Proposed Solution
N Task Point
Locations
M AUV
Locations
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Task
Assignment
Algorithm
M Task
Assignments
Task
Sequence
Algorithm
M Task
Sequences
AUV Path
Construction
Algorithm
M AUV
Paths
Proposed Solution
 Task Assignment Algorithm
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Cluster N points into M groups K-means clustering
algorithm
Assign one AUV to each cluster using a greedy
assignment algorithm
 Task Sequence Algorithm
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Find next closest point algorithm
 AUV Path Construction Algorithm
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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
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Milestones
Data
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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