In the context of Mobile Robotics, the efficient resolution of the Path Planning problem is a key task. The model of the environment and the search algorithm are basic issues in the resolution of the problem. This paper highlights the main features of Path Planning proposal for mobile robots in static environments. In our proposal, the path planning is based on Voronoi diagrams, where obstacles in the environment are considered as the generating points of the diagram, and a genetic algorithm is used to find a path without collisions from the robot initial to target position. This work combines some ideas presented by Roque and Doering, who use Voronoi diagrams for modelling the environment, and other ideas presented by Zhang et al. who adopt a genetic algorithm for computing paths on a regular grid based environment, considering certain quality attributes. The main results were probed both in simulated and real environments.
The exploration problem is a fundamental subject in autonomous mobile robotics that deals with achieving the complete coverage of a previously unknown environment. There are several scenarios where completing exploration of a zone is a main part of the mission. Due to the efficiency and robustness brought by multi-robot systems, exploration is usually done cooperatively. Wireless communication plays an important role in collaborative multi-robot strategies. Unfortunately, the assumption of stable communication and end-to-end connectivity may be easily compromised in real scenarios. In this paper, a novel auto-adaptive multi-objective strategy is followed to support the selection of tasks regarding both exploration performance and connectivity level. Compared with others, the proposed approach shows effectiveness and flexibility to tackle the multi-robot exploration problem, being capable of decreasing the last of disconnection periods without noticeable degradation of the completion exploration time.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.