Ergodic Search

Ergodic search is a robotic exploration strategy aiming to optimize the time spent in different areas of a search space, proportionally to the information value of each area. Current research focuses on improving the efficiency and robustness of ergodic search algorithms, addressing challenges such as obstacle avoidance, handling disturbances, and incorporating multiple objectives (e.g., time constraints, energy limitations, multiple information sources). These advancements leverage techniques like variational inference, reachability analysis, kernel methods, and model predictive control to generate efficient and adaptable exploration trajectories, with applications in diverse fields including search and rescue, environmental monitoring, and autonomous surveying.