Terrain Based Planning of Mars Rover Platform
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School of Electrical Engineering |
Master's thesis
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Mcode
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en
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50
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Abstract
The space industry has seen remarkable growth, but human-led space exploration remains in the early stages due to high costs and complex challenges. In contrast, robotic missions, such as NASA’s Perseverance rover, are actively advancing space research at a fraction of the cost, leveraging autonomy for path planning and navigation. These advancements in robotics are crucial for future missions on Mars and beyond. However, existing path planning methods, such as grid-based and sampling-based planners, face limitations in terms of computational cost, real-time performance, and efficiency. Model Predictive Control (MPC), known for its ability to handle constraints and optimize complex systems, presents a promising alternative. This thesis evaluates the feasibility of using MPC for autonomous path planning in space rover platforms, focusing on its integration with environment perception and experimental evaluation in both simulation and physical tests. The results of this research aim to enhance rover autonomy for future deep space missions, demonstrating the potential of MPC as an efficient and adaptable solution for planetary exploration.Description
Supervisor
Kyrki, VilleThesis advisor
Satpute, SumeetBanerjee, Avijit