Tangle- and contact-free path planning for a tethered mobile robot using deep reinforcement learningdoi:10.3389/frobt.2024.1388634Shimada, RyukiIshigami, GenyaUriguen, PedroRoveri, MarcoFrontiers in Robotics & AI
Exact and approximate algorithms are presented, whose solution is further demonstrated on a physical tethered aerial vehicle. Other than the visual assistance problem, the proposed framework also provides a new planning paradigm to address minimum-risk planning under dynamical risk and absence of ...
SpiderBot’s dependence on gravity, its secondary mechanism, and its motion planning approach makes it unsuited for space environments with sparse anchor points. Oda et al. [5] introduced Astrobot, an incompletely restrained four-cable climbing robot designed as a servicing robot for both the ...
Tangle-Free Exploration with a Tethered Mobile Robot. Remote Sens. 2020, 12, 3858. [Google Scholar] [CrossRef] Bai, S.; Wang, J.; Chen, F.; Englot, B. Information-theoretic exploration with Bayesian optimization. In Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent ...
They are propelled by flapping wings and at this stage are usually tethered to a power source. While this is an impressive MAV, it is far from capable of autonomous pollination, as it is too small to carry a microchip for decision making and is constrained either by a tether or small ...
fault-tolerant; multi-agent systems; coverage path planning; reinforcement learning 1. Introduction Exploration of Mars presents myriad opportunities for advancement in fields such as innovation, culture, and technology. The endeavor to decipher the geology, climate, and potential for harboring life, ...