TR2025-170
Motion Planning for Information Acquisition via Continuous-time Successive Convexification
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- , "Motion Planning for Information Acquisition via Continuous-time Successive Convexification", IEEE Conference on Decision and Control (CDC), December 2025.BibTeX TR2025-170 PDF
- @inproceedings{Uzun2025dec,
- author = {Uzun, Samet and Acikmese, Behcet and {Di Cairano}, Stefano},
- title = {{Motion Planning for Information Acquisition via Continuous-time Successive Convexification}},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2025,
- month = dec,
- url = {https://www.merl.com/publications/TR2025-170}
- }
- , "Motion Planning for Information Acquisition via Continuous-time Successive Convexification", IEEE Conference on Decision and Control (CDC), December 2025.
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Abstract:
We address motion planning for a mobile agent to acquire information from multiple monitored tar- gets using sensors with limited capabilities. To represent sensor limitations, such as range, field of view, and allowed acquisition directions, we introduce a nonnegative metric that quantifies the rate of information acquisition and is positive only when these limitations are satisfied. To en- able optimization-based trajectory generation, we impose temporal logic specifications to ensure that the information acquisition metric and its gradient are nonzero over some time interval. This enables the application of continuous- time successive convexification to solve the motion planning problem. We demonstrate the proposed approach in a case study of a quadrotor that must acquire information on multiple targets with sensor range, field of view, and acquisition direction constraints.
