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Constraint-Based Motion Planning for Multiple Agents. Luv Kohli COMP290-058 September 29, 2003. Constraint-based?. Garber & Lin formulated the motion planning problem as a dynamical system simulation
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Constraint-Based Motion Planning for Multiple Agents Luv Kohli COMP290-058 September 29, 2003
Constraint-based? • Garber & Lin formulated the motion planning problem as a dynamical system simulation • Each robot is a rigid body or a collection of rigid bodies influenced by constraint forces in the environment
Constraints • Hard constraints • Absolutely must be satisfied (e.g. non-penetration, articulated robot joint connectivity) • Soft constraints • Encourage objects to follow certain behaviors (e.g. moving towards a goal, obstacle avoidance)
Multiple agents • I would like to extend the constraint-based framework to study scenarios involving multiple interacting agents • Possible scenarios: • Team rescue operations – compromised senses • Game scenarios (e.g., sports) • Military operations – continuous line of sight
What’s this all for, anyway? • If the constraints of a real multiple-agent system can be identified and modeled, then the feasibility of the goal can be studied • Virtual environments • Games
Tasks • Minimally I would like to get a constraint-based system working with multiple agents • The multiple agents will be acting either against each other or with one another towards some global goal, but influenced by local behavior
Behavior and Intelligence • It would be interesting to add higher levels of behavior and intelligence • Flocking-style algorithms • Agents that learn skills that can be applied to multiple scenarios
Simple example Field of view communication
Steps • Create a working constraint-based system • Create a constraint for line of sight, and get multiple agents to interact under the influence of this constraint • Determine how behaviors (e.g. information gathering) relate to constraint model • Implement new constraints
References • Garber, M. and Lin, M. Constraint-Based Motion Planning using Voronoi Diagrams. Proc. Fifth International Workshop on Algorithmic Foundations of Robotics (WAFR), 2002. • Garber, M. and Lin, M. Constraint-Based Motion Planning for Virtual Prototyping. Proc. ACM Symposium on Solid Modeling and Applications, 2002. • Reynolds, C. W.. Flocks, Herds, and Schools: A Distributed Behavioral Model. Computer Graphics, 21(4): 25-34, 1987. • Goldenstein, S., Large, E., and Metaxas, D. Dynamic Autonomous Agents: Game Applications. Computer Animation, 1998.