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DaSP-RRT : Data-driven Safe Performance-aware Motion Planning
Author(s) -
Nariman Niknejad,
Ramin Esmzad,
Teawon Han,
Gokul S. Sankar,
Hamidreza Modares
Publication year - 2025
Publication title -
ieee robotics and automation letters
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 1.123
H-Index - 56
eISSN - 2377-3766
DOI - 10.1109/lra.2025.3595041
Subject(s) - robotics and control systems , computing and processing , components, circuits, devices and systems
This letter presents a data-driven safe motion planning approach, DaSP-RRT , 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 DaSP-RRT 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.

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