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DaSP-RRT: Data-Driven Safe Performance-Aware Motion Planning
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DOI：10.1109/LRA.2025.3595041.png)
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Abstract
En 中文
This letter presents a data-driven safe motion planning approach, <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DaSP-RRT</monospace>, designed to generate collision-free paths with guaranteed optimality through the use of invariant sets. The proposed planner constructs a sequence of performance-aware invariant sets using available data and a new control design approach. These sets are centered around randomly generated waypoints, which are then connected to form a continuous path from the initial to the target point. For each waypoint, an optimization problem determines the largest performance-aware invariant set and learns its corresponding controller. A key feature of the algorithm is its incorporation of performance-reachability between connected waypoints, leveraging available resources and system information to minimize the need for frequent re-planning. The effectiveness of <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DaSP-RRT</monospace> is demonstrated through a real-world implementation on an omnidirectional wheeled robot and simulations on spacecraft motion planning. These scenarios, which include obstacle avoidance, highlight the algorithm's potential for practical, real-world applications.
Keywords:
Motion planning
invariant sets
linear matrix inequalities (LMIs)
optimization
optimal control
safe control
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