Title
Bernstein Polynomial-Based Method for Solving Optimal Trajectory Generation Problems
Abstract
This paper presents a method for the generation of trajectories for autonomous system operations. The proposed method is based on the use of Bernstein polynomial approximations to transcribe infinite dimensional optimization problems into nonlinear programming problems. These, in turn, can be solved using off-the-shelf optimization solvers. The main motivation for this approach is that Bernstein polynomials possess favorable geometric properties and yield computationally efficient algorithms that enable a trajectory planner to efficiently evaluate and enforce constraints along the vehicles' trajectories, including maximum speed and angular rates as well as minimum distance between trajectories and between the vehicles and obstacles. By virtue of these properties and algorithms, feasibility and safety constraints typically imposed on autonomous vehicle operations can be enforced and guaranteed independently of the order of the polynomials. To support the use of the proposed method we introduce BeBOT (Bernstein/Bezier Optimal Trajectories), an open-source toolbox that implements the operations and algorithms for Bernstein polynomials. We show that BeBOT can be used to efficiently generate feasible and collision-free trajectories for single and multiple vehicles, and can be deployed for real-time safety critical applications in complex environments.
Year
DOI
Venue
2022
10.3390/s22051869
SENSORS
Keywords
DocType
Volume
optimal trajectory generation, Bernstein polynomials, Bezier curves, optimal control
Journal
22
Issue
ISSN
Citations 
5
1424-8220
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Calvin Kielas-Jensen101.01
Venanzio Cichella200.34
Thomas Berry300.34
Isaac Kaminer48214.50
Claire Walton500.34
Antonio Pascoal600.34