Chaotic Grey Wolf Optimizer Steers Robot Boats and Underwater Vehicles Through Disturbances
A new simulation study shows that a disturbance-observer-based adaptive neuro-fuzzy sliding mode controller tuned by a chaotic grey wolf optimizer ...
A new simulation study shows that a disturbance-observer-based adaptive neuro-fuzzy sliding mode controller tuned by a chaotic grey wolf optimizer ...
A simulation study found that a PID-and-reactive navigation scheme kept a mobile robot collision-free but slowed it to 0.17 m/s ...
A modular path-planning framework called LKSD-PRRT* achieved a 100% static planning success rate and cut dynamic recovery time by 77.25% ...
A hybrid of probabilistic roadmaps and bidirectional A* search produced shorter paths and faster planning times than Dijkstra-based and conventional ...
A MATLAB simulation combining Theta* planning, potential field avoidance, Pure Pursuit tracking and LIDAR mapping reached the goal in nine ...
Researchers report a simulation-only control framework, RISMO, that coordinates UAV-UGV swarms through unknown non-convex environments using a Fisher-information-shaped Riemannian metric, ...
Researchers have built a computational model based on stochastic optimal control that reproduces how human movements bend around obstacles while ...
An enhanced asynchronous actor-critic framework trained in simulation and on a physical mobile robot showed faster convergence, higher throughput, and ...
A new reinforcement learning method called FA-PPO was the only tested algorithm to complete simulated UAV obstacle-avoidance tasks across three ...
Researchers combined artificial potential field trajectory planning with a discrete integral terminal sliding mode controller to let a Mecanum-wheeled omnidirectional ...
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© 2025 Scienmag - Science Magazine