Author:
Andreasen Malte Z.,Holler Philip I.,Jensen Magnus K.,Albano Michele
Abstract
AbstractWith the aim of allowing the efficient and realistic simulation of swarm algorithms for exploration and coverage, we present the tool Multi-Agent Exploration Simulator (MAES), which is an open-source physics-based discrete step multi-robot simulator. MAES features movement in a continuous 2D space, realistic physics based on the Unity framework, advanced visualization techniques such as heatmaps, custom wireless signal degradation, both randomly generated and custom user-provided maps, and a ROS (Robot Operating System) interface. This latter characteristic could allow to port the simulated algorithms to real-world robots. We present performance tests, conducted with rather modest hardware, showing that MAES is able to simulate up to 5 robots in ROSMode (using the ROS integration) and up to 120 robots in UnityMode (development performed directly into the C# Unity Editor). A usability test was conducted which hinted that the target audience of robotics researchers and developers is able to quickly install, setup, and use MAES for implementing simple robot logic.
Funder
Open access funding provided by Aalborg University Library.
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,General Biochemistry, Genetics and Molecular Biology
Reference31 articles.
1. ARGoS (2022) Argos - large-scale robot simulations. https://www.argos-sim.info. Accessed 29 Aug 2023
2. Open Robotics (2022a) Gazebo - simulate before you build. https://gazebosim.org/home. Accessed 29 Aug 2023
3. Agmon N, Hazon N, Gal KA (2008) The giving tree: constructing trees for efficient offline and online multi-robot coverage. Annals Mathemat Artif Intell 52(2):143–168
4. Dorigo M, Guy T, Vito T (2021) Swarm robotics: past, present, and future [point of view]. Proc IEEE 109(7):1152–1165
5. Schranz M, Di Caro GA, Thomas S, Wilfried E, Farshad A, Ahmet Ş, Micha S (2021) Swarm intelligence and cyber-physical systems: concepts, challenges and future trends. Swarm Evolut Comput 60:100762
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献