Advancements in the field of robotics together with an increased need for surveillance have lead to an interest in utilizing autonomous agents for area monitoring at sensitive installations. For this Master's thesis, an informative path planner called Autonomous Surveillance Planner (ASP) was developed to be used with unmanned ground vehicles for area monitoring. It discretizes an area of operations into cells and assigns each cell an intruder probability. The planner then chooses the optimal path by minimizing a cost function describing the probability of not finding an intruder along a path. Since the minimization is computationally costly, the computed path does not cover the entire area but instead only a small portion at a time. The path from the ASP is then relayed to a timed elastic band local planner which adjusts the path such that it avoids obstacles and is fast for an agent to execute, as well as computes control signals. The algorithms were tested both in simulations and during field tests with promising results, showcasing that using unmanned ground vehicles for autonomous area monitoring has potential to be used in a real-world application. ASP was fast enough to be used in real-time and was able to fully cover the area of operations. The local planner was computationally demanding, but was able to avoid obstacles and make the agent follow the global path. / <p>Opponent: Samuel Ericson Andersson</p>
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-204988 |
| Date | January 2024 |
| Creators | Wiman, David |
| Publisher | Linköpings universitet, Reglerteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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