TR2025-170

Motion Planning for Information Acquisition via Continuous-time Successive Convexification


    •  Uzun, S., Acikmese, B., Di Cairano, S., "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}
      • }
  • MERL Contact:
  • Research Areas:

    Control, Dynamical Systems, Optimization, Robotics

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.