koes06icra - Constraint Optimization Coordination...

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Unformatted text preview: Constraint Optimization Coordination Architecture for Search and Rescue Robotics Mary Koes, Illah Nourbakhsh, and Katia Sycara Carnegie Mellon Robotics Institute Pittsburgh, PA { mberna, illah, katia } @cs.cmu.edu Abstract — The dangerous and time sensitive nature of a disaster area makes it an ideal application for robotic exploration. Our long term goal is to enable humans, software agents, and autonomous robots to work together to save lives. Existing work in coordination for search and rescue does not address the variety of constraints that apply to the problem. This paper provides an expressive language for specifying system constraints. We also describe a coordination architecture capable of quickly finding an optimal or near optimal solution to the combined problems of task allocation, scheduling, and path planning subject to system constraints. We address a perceived lack of benchmarks for this research area by establishing a repository open to the research community which includes a set of benchmarks we designed to illustrate some of the complexities of the problem space. Finally, we evaluate various algorithms on these benchmarks. Following a natural or man made disaster, rescue workers risk their lives searching for survivors in a race against time. The search and rescue domain has the potential to benefit greatly from robotic technology. Our vision is that robots could use a rough map of the environment, perhaps obtained from a blueprint or city map, and search areas specified by human rescue workers. This problem not only has significant humanitarian benefits but poses a difficult research challenge. Robot teams in chal- lenging environments such as disaster sites will necessarily be heterogeneous as cost limitations, power consumption, and size constraints require tradeoffs between mobility and capabilities. Large scale disasters need to include robots with diverse modalities (e.g. ground, air, water). Multiple robots are often required to work together on a joint goal . Coordination on a joint goal involves simultaneously solving two NP-hard problems, task allocation and scheduling, as well as the path planning problem [1]. Since each passing minute reduces the chance of success- fully rescuing victims, the quality of the solution is very important. Furthermore, the system must accommodate a wide variety of system constraints on goals, robots, and resources. A problem formulation that does not allow for these constraints is, for example, unable to handle the simple constraint, turn off the circuit breakers before completing any other goals. These four aspects of the problem–heterogeneity, joint tasks, emphasis on optimality, and additional system constraints– distinguish the problem from other multirobot planning prob- lems. Research in market-based algorithms for coordination [2] and token based coordination algorithms [3] cannot effi- ciently reason about joint goals....
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This note was uploaded on 08/25/2011 for the course EGN 3060c taught by Professor Sukthankar,g during the Fall '08 term at University of Central Florida.

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koes06icra - Constraint Optimization Coordination...

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