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Path planning of a mobile robot under dynamic environment is a difficult part of robot navigation. In this paper, a new path planning method based on improved Q-learning (IQL) algorithm and some heuristic searching strategies is proposed for mobile robot in dynamic environment. A new exploration strategy which combines ε-greedy exploration with Boltzmann exploration is used in IQL. In addition, the...
This paper presents a novel motion planning method, based on heuristic dynamic programming (HDP), applicable to the control of wheeled mobile robots (WMRs). First, a new architecture of motion planning system is proposed, where the motion planner is designed based on the HDP algorithm. Second, we devise a reward function, which is beneficial for improving the planning efficiency. Then, back propagation...
This paper addresses the problem of autonomous tracking a set of ground static targets using minimal fixed wing unmanned aerial vehicles(UAVs). Each target is tracked loosely and has its desired revisit interval. Due to the UAV's dynamic constrains of fixed wing, it is modeled as a Dubins car. The motion planing of UAVs is a NP hard problem to find the shortest path, i.e. Dubins path. Because of the...
During the past decade, Rapidly-exploring Random Tree (RRT) and its variants are shown to be powerful sampling based single query path planning approaches for robots in high-dimensional configuration space. However, the performance of such tree-based planners that rely on uniform sampling strategy degrades significantly when narrow passages are contained in the configuration space. Given the assumption...
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