Decentralized coordinated tracking with mixed discrete-continuous decisions

Publication Type:
Journal Article
Citation:
Journal of Field Robotics, 2013, 30 (5), pp. 717 - 740
Issue Date:
2013-09-01
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The article examines the problem of dynamically positioning a team of mobile robots for target tracking. The optimization is inherently a function of both the positioning of robots in continuous space and the assignment of robots to targets in discrete space. In information-gathering tasks, a coordinated team of robots has clear advantages over any single robot. A single robot is forced to spread its attention among the targets being tracked, whereas a team of robots can divide-and conquer. Another advantage of teams is that they provide redundancy in case of individual robot failures, but only if the team is decentralized. One motivating example is the coordination of unmanned ground vehicles (UGV) to track pedestrians moving in a semiurban environment. Additionally, these approaches to solving the MINLP are centralized, while one wishes to have a decentralized solution. Thus, the challenge is to find a computationally efficient approximation to the MINLP that operates in a decentralized manner.
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