Three Dimensional Robot Path Planning With Workspace Considerations

Author(s):  
C. Y. Liu ◽  
R. W. Mayne

Abstract This paper considers the problem of robot path planning by optimization methods. It focuses on the use of recursive quadratic programming (RQP) for the optimization process and presents a formulation of the three dimensional path planning problem developed for compatibility with the RQP selling. An approach 10 distance-to-contact and interference calculations appropriate for RQP is described as well as a strategy for gradient computations which are critical to applying any efficient nonlinear programming method. Symbolic computation has been used for general six degree-of-freedom transformations of the robot links and to provide analytical derivative expressions. Example problems in path planning are presented for a simple 3-D robot. One example includes adjustments in geometry and introduces the concept of integrating 3-D path planning with geometric design.

2018 ◽  
Vol 160 ◽  
pp. 06004
Author(s):  
Zi-Qiang Wang ◽  
He-Gen Xu ◽  
You-Wen Wan

In order to solve the problem of warehouse logistics robots planpath in different scenes, this paper proposes a method based on visual simultaneous localization and mapping (VSLAM) to build grid map of different scenes and use A* algorithm to plan path on the grid map. Firstly, we use VSLAMto reconstruct the environment in three-dimensionally. Secondly, based on the three-dimensional environment data, we calculate the accessibility of each grid to prepare occupied grid map (OGM) for terrain description. Rely on the terrain information, we use the A* algorithm to solve path planning problem. We also optimize the A* algorithm and improve algorithm efficiency. Lastly, we verify the effectiveness and reliability of the proposed method by simulation and experimental results.


Author(s):  
Masakazu Kobayashi ◽  
Higashi Masatake

A robot path planning problem is to produce a path that connects a start configuration and a goal configuration while avoiding collision with obstacles. To obtain a path for robots with high degree of freedom of motion such as an articulated robot efficiently, sampling-based algorithms such as probabilistic roadmap (PRM) and rapidly-exploring random tree (RRT) were proposed. In this paper, a new robot path planning method based on Particle Swarm Optimization (PSO), which is one of heuristic optimization methods, is proposed in order to improve efficiency of path planning for a wider range of problems. In the proposed method, a group of particles fly through a configuration space while avoiding collision with obstacles and a collection of their trajectories is regarded as a roadmap. A velocity of each particle is updated for every time step based on the update equation of PSO. After explaining the details of the proposed method, this paper shows the comparisons of efficiency between the proposed method and RRT for 2D maze problems and then shows application of the proposed method to path planning for a 6 degree of freedom articulated robot.


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