biostudies-literatureUnknown9Ataka AOver the course of the past decade, we have witnessed a huge expansion in robotic applications, most notably from well-defined industrial environments into considerably more complex environments. The obstacles that these environments often contain present robotics with a new challenge - to equip robots with a real-time capability of avoiding them. In this paper, we propose a magnetic-field-inspired navigation method that significantly has several advantages over alternative systems. Most importantly, 1) it guarantees obstacle avoidance for both convex and non-convex obstacles, 2) goal convergence is still guaranteed for point-like robots in environments with convex obstacles and non-maze concave obstacles, 3) no prior knowledge of the environment, such as the position Frontiers in robotics and AI834177https://www.ebi.ac.uk/biostudies/studies/S-EPMC8894445biostudies-literatureMagnetic-Field-Inspired Navigation for Robots in Complex and Unknown Environments.PMC8894445Lam HKAtaka AAlthoefer KfalseMagnetic-Field-Inspired Navigation for Robots in Complex and Unknown Environments.Over the course of the past decade, we have witnessed a huge expansion in robotic applications, most notably from well-defined industrial environments into considerably more complex environments. The obstacles that these environments often contain present robotics with a new challenge - to equip robots with a real-time capability of avoiding them. In this paper, we propose a magnetic-field-inspired navigation method that significantly has several advantages over alternative systems. Most importantly, 1) it guarantees obstacle avoidance for both convex and non-convex obstacles, 2) goal convergence is still guaranteed for point-like robots in environments with convex obstacles and non-maze concave obstacles, 3) no prior knowledge of the environment, such as the position 2022-01-01T00:00:00Z20222025-04-05T13:09:35.464Z2025-04-05T13:09:35.464ZS-EPMC88944453525236610.3389/frobt.2022.834177