Conference proceeding
Scalable Trajectory Planning for Multi-Agent Systems Using Continuum Mechanics and Bernstein Polynomials
Proceedings of the IEEE Conference on Decision & Control, pp.1570-1575
12/09/2025
DOI: 10.1109/CDC57313.2025.11312044
Abstract
When tackling the issue of scalability in trajectory planning for large numbers of agents, generation of continuous surfaces from partial differential equation solutions has become increasingly popular. In this work, a framework borrowing from principles of continuum dynamics is proposed for scalable trajectory generation of multi-agent systems. The problem is presented as an optimal control problem (OCP), transcribed to a nonlinear programming (NLP) problem with Bernstein polynomials, which gives a solution as a time-dependent solid. This solution inherently guarantees inter-agent collision avoidance and leverages the unique properties of the Bernstein basis to ensure adherence to constraints including obstacle collision avoidance.
Details
- Title: Subtitle
- Scalable Trajectory Planning for Multi-Agent Systems Using Continuum Mechanics and Bernstein Polynomials
- Creators
- Maxwell Hammond - University of IowaGage MacLin - University of IowaAmirreza F. Golestaneh - University of IowaVenanzio Cichella - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the IEEE Conference on Decision & Control, pp.1570-1575
- DOI
- 10.1109/CDC57313.2025.11312044
- eISSN
- 2576-2370
- Publisher
- IEEE
- Grant note
- Office of Naval Research (10.13039/100000006)
- Language
- English
- Date published
- 12/09/2025
- Academic Unit
- Mechanical Engineering
- Record Identifier
- 9985130057602771
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