Abstract
Local path planning is important in the development of autonomous vehicles since it allows a vehicle to adapt their movements to dynamic environments, for instance, when obstacles are detected. This work presents an evaluation of the performance of different local path planning techniques for an Autonomous Surface Vehicle, using a custom-made simulator based on the open-source Robotarium framework. The conducted simulations allow to verify, compare and visualize the solutions of the different techniques. The selected techniques for evaluation include A*, Potential Fields (PF), Rapidly-Exploring Random Trees* (RRT*) and variations of the Fast Marching Method (FMM), along with a proposed new method called Updating the Fast Marching Square method (uFMS). The evaluation proposed in this work includes ways to summarize time and safety measures for local path planning techniques. The results in a Lake environment present the advantages and disadvantages of using each technique. The proposed uFMS and A* have been shown to achieve interesting performance in terms of processing time, distance travelled and security levels. Furthermore, the proposed uFMS algorithm is capable of generating smoother routes.
Highlights
Nowadays numerous applications including data collecting, intelligent transport systems, monitoring of water masses, disaster relief and surveillance, among others, are accomplished by the use of unmanned vehicles, both aerial and/or aquatic vehicles [1]
Findings reveal that according to the obtained results, the most attractive ones are the A* and the proposed Updating the Fast Marching Square method (uFMS)
The first one finds shorter routes in low computational time, the proposed uFMS provides in general better levels of security
Summary
Nowadays numerous applications including data collecting, intelligent transport systems, monitoring of water masses, disaster relief and surveillance, among others, are accomplished by the use of unmanned vehicles, both aerial and/or aquatic vehicles [1]. Unmanned vehicles present important advantages, such as low cost in terms of hardware since they usually have smaller dimensions compared with classical vehicles, and they do not need personnel on board since they are self-managed. They do require an increase of complexity for the control system. When multiple vehicles cooperate each other, they can form swarms, working in a centralized or distributed way to accomplish a target mission efficiently [6] They can act as a communication repeater or extender in a network of autonomous vehicles [7]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
