Conference proceeding
On-Line Motion Planning Using Bernstein Polynomials for Enhanced Target Localization in Autonomous Vehicles
2024 American Control Conference (ACC), pp.1398-1403
07/10/2024
DOI: 10.23919/ACC60939.2024.10644986
Abstract
The use of autonomous vehicles for target localization in modern applications has emphasized their superior efficiency, improved safety, and cost advantages over human-operated methods. For localization tasks, autonomous vehicles can be used to increase efficiency and ensure that the target is localized as quickly and precisely as possible. However, devising a motion planning scheme to achieve these objectives in a computationally efficient manner suitable for real-time implementation is not straightforward. In this paper, we introduce a motion planning solution for enhanced target localization, leveraging Bernstein polynomial basis functions to approximate the probability distribution of the target's trajectory. This allows us to derive estimation performance criteria which are used by the motion planner to enhance the estimator efficacy. To conclude, we present simulation results that validate the effectiveness of the suggested algorithm.
Details
- Title: Subtitle
- On-Line Motion Planning Using Bernstein Polynomials for Enhanced Target Localization in Autonomous Vehicles
- Creators
- Camilla Tabasso - University of IowaVenanzio Cichella - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- 2024 American Control Conference (ACC), pp.1398-1403
- Publisher
- AACC
- DOI
- 10.23919/ACC60939.2024.10644986
- eISSN
- 2378-5861
- Number of pages
- 6
- Grant note
- N000142112091 / Office of Naval Research (10.13039/100000006)
- Language
- English
- Date published
- 07/10/2024
- Academic Unit
- Mechanical Engineering
- Record Identifier
- 9984702834002771
Metrics
2 Record Views