Title
Scalarizing Multi-Objective Robot Planning Problems Using Weighted Maximization
Author
Wilde, N. (TU Delft Learning & Autonomous Control)
Smith, Stephen L. (University of Waterloo)
Alonso-Mora, J. (TU Delft Learning & Autonomous Control) 
Date
2024
Abstract
When designing a motion planner for autonomous robots there are usually multiple objectives to be considered. However, a cost function that yields the desired trade-off between objectives is not easily obtainable. A common technique across many applications is to use a weighted sum of relevant objective functions and then carefully adapt the weights. However, this approach may not find all relevant trade-offs even in simple planning problems. Thus, we study an alternative method based on a weighted maximum of objectives. Such a cost function is more expressive than the weighted sum, and we show how it can be deployed in both continuous-and discrete-space motion planning problems. We propose a novel path planning algorithm for the proposed cost function and establish its correctness, and present heuristic adaptations that yield a practical runtime. In extensive simulation experiments, we demonstrate that the proposed cost function and algorithm are able to find a wider range of trade-offs between objectives (i.e., Pareto-optimal solutions) for various planning problems, showcasing its advantages in practice.
Subject
motion and path planning
multi-objective optimization
Optimization and optimal control
task and motion planning
To reference this document use:
http://resolver.tudelft.nl/uuid:62205fc4-ab38-49b8-ae91-047740e60497
DOI
https://doi.org/10.1109/LRA.2024.3357313
Embargo date
2024-07-23
ISSN
2377-3766
Source
IEEE Robotics and Automation Letters, 9 (3), 2503-2510
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2024 N. Wilde, Stephen L. Smith, J. Alonso-Mora