
Deriving analytical backpropagation equations for EKF covariance gradients enables perception-aware optimal motion planning.


coremsg

backpropagation-based-analytical-derivatives-of-ekf-covariance-for-active-sensing-enhancing-robot-state-estimation-accuracy


Backpropagation-Based Analytical Derivatives of EKF Covariance for Active Sensing: Enhancing Robot State Estimation Accuracy


title_rewrite


Learning-based NNPP model reduces search time for optimal paths on planetary surfaces.


fast-and-optimal-learning-based-path-planning-for-planetary-rovers


Fast and Optimal Learning-based Path Planning for Planetary Rovers



Efficient path planning for autonomous robots in dynamic environments is achieved by considering environmental flow fields and obstacles, optimizing both time and energy simultaneously.


efficient-path-planning-in-dynamic-environments-with-flow-fields


Efficient Path Planning in Dynamic Environments with Flow Fields



Introducing a novel PF-DDQN method for multi-AGV path planning, enhancing efficiency and outperforming traditional DDQN algorithms.


efficient-multi-agv-path-planning-method-with-reinforcement-learning-and-particle-filters


Efficient Multi-AGV Path Planning Method with Reinforcement Learning and Particle Filters
