OBPRM: an obstacle-based PRM for 3D workspaces
WAFR '98 Proceedings of the third workshop on the algorithmic foundations of robotics on Robotics : the algorithmic perspective: the algorithmic perspective
3D mapping with multi-resolution occupied voxel lists
Autonomous Robots
6D scan registration using depth-interpolated local image features
Robotics and Autonomous Systems
An Improved Heuristic Algorithm for UAV Path Planning in 3D Environment
IHMSC '10 Proceedings of the 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics - Volume 02
RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments
International Journal of Robotics Research
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Ground Target Tracking Using UAV with Input Constraints
Journal of Intelligent and Robotic Systems
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This paper presents a 3D path planning algorithm for an unmanned aerial vehicle (UAV) in complex environments. In this algorithm, the environments are divided into voxels by octree algorithm. In order to satisfy the safety requirement of the UAV, free space is represented by free voxels, which have enough space margin for the UAV to pass through. A bounding box array is created in the whole 3D space to evaluate the free voxel connectivity. The probabilistic roadmap method (PRM) is improved by random sampling in the bounding box array to ensure a more efficient distribution of roadmap nodes in 3D space. According to the connectivity evaluation, the roadmap is used to plan a feasible path by using A* algorithm. Experimental results indicate that the proposed algorithm is valid in complex 3D environments.