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Conference Paper: Encirclement Guaranteed Cooperative Pursuit with Robust Model Predictive Control
Title | Encirclement Guaranteed Cooperative Pursuit with Robust Model Predictive Control |
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Authors | |
Keywords | Path Planning for Multiple Mobile Robots or Agents Multi-Robot Systems Cooperating Robots |
Issue Date | 2021 |
Publisher | IEEE Robotics & Automation Society. |
Citation | 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Virtual Conference, Prague, Czech Republic, 27 September - 1 October 2021 How to Cite? |
Abstract | This paper studies a novel encirclement guaranteed cooperative pursuit problem involving N pursuers and a single evader in an unbounded two-dimensional game domain. Throughout the game, the pursuers are required to maintain encirclement of the evader, i.e., the evader should always stay inside the convex hull generated by all the pursuers, in addition to achieving the classical capture condition. To tackle this challenging cooperative pursuit problem, a robust model predictive control (RMPC) based formulation framework is first introduced, which simultaneously accounts for the encirclement and capture requirements under the assumption that the evader's action is unavailable to all pursuers. Despite the reformulation, the resulting RMPC problem involves a bilinear constraint due to the encirclement requirement. To further handle such a bilinear constraint, a novel encirclement guaranteed partitioning scheme is devised that simplifies the original bilinear RMPC problem to a number of linear tube MPC (TMPC) problems solvable in a decentralized manner. Simulation experiments demonstrate the effectiveness of the proposed solution framework. Furthermore, comparisons with existing approaches show that the explicit consideration of the encirclement condition significantly improves the chance of successful capture of the evader in various scenarios. |
Description | TuBT8 Lecture Session: Multi-Robot Systems - Paper TuBT8.3 |
Persistent Identifier | http://hdl.handle.net/10722/301573 |
DC Field | Value | Language |
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dc.contributor.author | Wang, C | - |
dc.contributor.author | Chen, H | - |
dc.contributor.author | Pan, J | - |
dc.contributor.author | Zhang, W | - |
dc.date.accessioned | 2021-08-09T03:41:01Z | - |
dc.date.available | 2021-08-09T03:41:01Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Virtual Conference, Prague, Czech Republic, 27 September - 1 October 2021 | - |
dc.identifier.uri | http://hdl.handle.net/10722/301573 | - |
dc.description | TuBT8 Lecture Session: Multi-Robot Systems - Paper TuBT8.3 | - |
dc.description.abstract | This paper studies a novel encirclement guaranteed cooperative pursuit problem involving N pursuers and a single evader in an unbounded two-dimensional game domain. Throughout the game, the pursuers are required to maintain encirclement of the evader, i.e., the evader should always stay inside the convex hull generated by all the pursuers, in addition to achieving the classical capture condition. To tackle this challenging cooperative pursuit problem, a robust model predictive control (RMPC) based formulation framework is first introduced, which simultaneously accounts for the encirclement and capture requirements under the assumption that the evader's action is unavailable to all pursuers. Despite the reformulation, the resulting RMPC problem involves a bilinear constraint due to the encirclement requirement. To further handle such a bilinear constraint, a novel encirclement guaranteed partitioning scheme is devised that simplifies the original bilinear RMPC problem to a number of linear tube MPC (TMPC) problems solvable in a decentralized manner. Simulation experiments demonstrate the effectiveness of the proposed solution framework. Furthermore, comparisons with existing approaches show that the explicit consideration of the encirclement condition significantly improves the chance of successful capture of the evader in various scenarios. | - |
dc.language | eng | - |
dc.publisher | IEEE Robotics & Automation Society. | - |
dc.relation.ispartof | IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021 | - |
dc.subject | Path Planning for Multiple Mobile Robots or Agents | - |
dc.subject | Multi-Robot Systems | - |
dc.subject | Cooperating Robots | - |
dc.title | Encirclement Guaranteed Cooperative Pursuit with Robust Model Predictive Control | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Pan, J: jpan@cs.hku.hk | - |
dc.identifier.authority | Pan, J=rp01984 | - |
dc.identifier.hkuros | 324077 | - |