ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2403.16859
21
0

A Semi-Lagrangian Approach for Time and Energy Path Planning Optimization in Static Flow Fields

25 March 2024
V. C. D. S. Campos
Armando A. Neto
D. Macharet
ArXivPDFHTML
Abstract

Efficient path planning for autonomous mobile robots is a critical problem across numerous domains, where optimizing both time and energy consumption is paramount. This paper introduces a novel methodology that considers the dynamic influence of an environmental flow field and considers geometric constraints, including obstacles and forbidden zones, enriching the complexity of the planning problem. We formulate it as a multi-objective optimal control problem, propose a novel transformation called Harmonic Transformation, and apply a semi-Lagrangian scheme to solve it. The set of Pareto efficient solutions is obtained considering two distinct approaches: a deterministic method and an evolutionary-based one, both of which are designed to make use of the proposed Harmonic Transformation. Through an extensive analysis of these approaches, we demonstrate their efficacy in finding optimized paths.

View on arXiv
@article{campos2025_2403.16859,
  title={ A Semi-Lagrangian Approach for Time and Energy Path Planning Optimization in Static Flow Fields },
  author={ Víctor C. da S. Campos and Armando A. Neto and Douglas G. Macharet },
  journal={arXiv preprint arXiv:2403.16859},
  year={ 2025 }
}
Comments on this paper