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Task Re-allocation Methodologies for Teams of Autonomous Agents in Dynamic Environments
| Content Provider | Semantic Scholar |
|---|---|
| Author | Sheridan, Patricia K. |
| Copyright Year | 2011 |
| Abstract | Two on-line task re-allocation methodologies capable of re-allocating agents to tasks on-line for minimum task completion time in dynamic environments are presented herein. The first methodology, the Dynamic Nearest Neighbour (DNN) Policy, is proposed for the operation of a fleet of vehicles in a city-like application of the dial-a-ride problem. The second methodology, the Dynamic Re-Pairing Methodology (DRPM) is proposed for the interception of a group of mobile targets by a dynamic team of robotic pursuers, where the targets are assumed to be highly maneuverable with a priori unknown, but real-time trackable, motion trajectories. Extensive simulations and experiments have verified the DNN policy to be tangibly superior to the first-come-first-served and nearest neighbour policies in minimizing customer mean system time, and the DRPM to be tangibly efficient in the optimal dynamic re-pairing of multiple mobile pursuers to multiple mobile targets for minimum total interception time. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://tspace.library.utoronto.ca/bitstream/1807/29621/1/Sheridan_Patricia_Kristine_201106_MASc_thesis.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
