On the Application of Model Predictive Control to a Weighted Coverage Path Planning Problem
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866912619217027072 |
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| author | Schweppe, Kilian Moshagen, Ludmila Schildbach, Georg |
| author_facet | Schweppe, Kilian Moshagen, Ludmila Schildbach, Georg |
| contents | This paper considers the application of Model Predictive Control (MPC) to a weighted coverage path planning (WCPP) problem. The problem appears in a wide range of practical applications, including search and rescue (SAR) missions. The basic setup is that one (or multiple) agents can move around a given search space and collect rewards from a given spatial distribution. Unlike an artificial potential field, each reward can only be collected once. In contrast to a Traveling Salesman Problem (TSP), the agent moves in a continuous space. Moreover, he is not obliged to cover all locations and/or may return to previously visited locations. The WCPP problem is tackled by a new Model Predictive Control (MPC) formulation with so-called Coverage Constraints (CCs). It is shown that the solution becomes more effective if the solver is initialized with a TSP-based heuristic. With and without this initialization, the proposed MPC approach clearly outperforms a naive MPC formulation, as demonstrated in a small simulation study. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_08634 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | On the Application of Model Predictive Control to a Weighted Coverage Path Planning Problem Schweppe, Kilian Moshagen, Ludmila Schildbach, Georg Systems and Control Multiagent Systems Robotics 93-08 This paper considers the application of Model Predictive Control (MPC) to a weighted coverage path planning (WCPP) problem. The problem appears in a wide range of practical applications, including search and rescue (SAR) missions. The basic setup is that one (or multiple) agents can move around a given search space and collect rewards from a given spatial distribution. Unlike an artificial potential field, each reward can only be collected once. In contrast to a Traveling Salesman Problem (TSP), the agent moves in a continuous space. Moreover, he is not obliged to cover all locations and/or may return to previously visited locations. The WCPP problem is tackled by a new Model Predictive Control (MPC) formulation with so-called Coverage Constraints (CCs). It is shown that the solution becomes more effective if the solver is initialized with a TSP-based heuristic. With and without this initialization, the proposed MPC approach clearly outperforms a naive MPC formulation, as demonstrated in a small simulation study. |
| title | On the Application of Model Predictive Control to a Weighted Coverage Path Planning Problem |
| topic | Systems and Control Multiagent Systems Robotics 93-08 |
| url | https://arxiv.org/abs/2411.08634 |