Path Planning for Manipulator Robots in Cluttered Environments

2005 ◽  
Author(s):  
Samir Lahouar ◽  
Said Zeghloul ◽  
Lotfi Romdhane
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Planning Method ◽  
Search Process ◽  
Grid Cells ◽  
Heuristic Function ◽  
Search Mode ◽  
Cluttered Environments ◽  
Grid Sampling ◽  
Cluttered Environment

In this paper we propose a new path planning method for robot manipulators in cluttered environments, based on lazy grid sampling. Grid cells are built while searching for the path to the goal configuration. The proposed planner acts in two modes. A depth mode, while the robot is far from obstacles, makes it evolve toward its goal. While a width search mode becomes active when the robot gets close to an obstacle. This method provides the shortest path to go around the obstacle. It also reduces the gap between pre-computed grid methods and lazy grid methods. No heuristic function is needed to guide the search process. An example dealing with a robot in a cluttered environment is presented to show the efficiency of the method.

Planning the Shortest Path in Cluttered Environments: A Review and a Planar Convex Hull-Based Approach

2019 ◽  
Vol 19 (4) ◽  
Author(s):  
Nafiseh Masoudi ◽  
Georges M. Fadel ◽  
Margaret M. Wiecek
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Time Complexity ◽  
Optimal Path ◽  
Optimal Solution ◽  
Free Graph ◽  
Worst Case ◽  
Cluttered Environments ◽  
Planar Convex ◽  
Polyhedral Obstacles

Abstract Routing or path-planning is the problem of finding a collision-free and preferably shortest path in an environment usually scattered with polygonal or polyhedral obstacles. The geometric algorithms oftentimes tackle the problem by modeling the environment as a collision-free graph. Search algorithms such as Dijkstra’s can then be applied to find an optimal path on the created graph. Previously developed methods to construct the collision-free graph, without loss of generality, explore the entire workspace of the problem. For the single-source single-destination planning problems, this results in generating some unnecessary information that has little value and could increase the time complexity of the algorithm. In this paper, first a comprehensive review of the previous studies on the path-planning subject is presented. Next, an approach to address the planar problem based on the notion of convex hulls is introduced and its efficiency is tested on sample planar problems. The proposed algorithm focuses only on a portion of the workspace interacting with the straight line connecting the start and goal points. Hence, we are able to reduce the size of the roadmap while generating the exact globally optimal solution. Considering the worst case that all the obstacles in a planar workspace are intersecting, the algorithm yields a time complexity of O(n log(n/f)), with n being the total number of vertices and f being the number of obstacles. The computational complexity of the algorithm outperforms the previous attempts in reducing the size of the graph yet generates the exact solution.

Formation Vector Based Shortest Path-Planning in CGF Formation

2013 ◽  
Vol 756-759 ◽  
pp. 3351-3355
Author(s):  
Fei Jie ◽  
Zhao Han Lu ◽  
Bao Di Xie
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Approximation Method ◽  
Change Process ◽  
Simulation System ◽  
Planning Method ◽  
Experimental Results ◽  
The Poor ◽  
Improved Algorithm

In order to improve the poor reality and bad flexibility of the mapping relationship which matched entities with aim locations in traditional approximation method, the formation vector shortest path-planning method was presented in this paper. By analyzing the lack of aim path-planning in the approximation method, shortest path-planning was discussed and was improved by introducing the formation vector and the idea of pheromone. Furthermore, the improved algorithm was applied in a CGF simulation system. The experimental results showed that the mapping relationship had better reality and rationality and the possibility of collision was significantly reduced than the traditional formation change process.

scholarly journals Any-Angle Path Planning

AI Magazine ◽  
2013 ◽  
Vol 34 (4) ◽  
pp. 85-107 ◽  
Author(s):  
Alex Nash ◽  
Sven Koenig
Keyword(s):  
Video Games ◽  
Path Planning ◽  
Shortest Path ◽  
Grid Cells ◽  
Grid Graph ◽  
Planning Algorithm ◽  
Planning Algorithms ◽  
Planning Methodology ◽  
Path Planning Algorithm

In robotics and video games, one often discretizes continuous terrain into a grid with blocked and unblocked grid cells and then uses path-planning algorithms to find a shortest path on the resulting grid graph. This path, however, is typically not a shortest path in the continuous terrain. In this overview article, we discuss a path-planning methodology for quickly finding paths in continuous terrain that are typically shorter than shortest grid paths. Any-angle path-planning algorithms are variants of the heuristic path-planning algorithm A* that find short paths by propagating information along grid edges (like A*, to be fast) without constraining the resulting paths to grid edges (unlike A*, to find short paths).

Path Planning for Ground Simulation Objiect Based on A* Algorithm

2012 ◽  
Vol 229-231 ◽  
pp. 2019-2024 ◽  
Author(s):  
Zhi Qiang Zhao ◽  
Zhi Hua Liu ◽  
Jia Xin Hao
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Optimal Path ◽  
Planning Method ◽  
Heuristic Function ◽  
A Algorithm

In the process of ground simulation object maneuver simulation in large-scale operation simulation, an efficient path planning method based on A*algorithm is proposed. By means of introducing all kind of geography factors and security factors into heuristic function, the plan reaching method solves the problem of finding an optimal path under acquiring enemy's situation and terrain data. Experiment results show that it has effectively raised path planning speed of A* algorithm and the scheme is practical and feasible.

scholarly journals Automatic Parking Path Planning Based on Ant Colony Optimization and the Grid Method

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guo Liang Han
Keyword(s):  
Path Planning ◽  
Ant Colony Optimization ◽  
Shortest Path ◽  
Grid Method ◽  
Path Tracking ◽  
Planning Method ◽  
Ant Colony ◽  
Planning Problem ◽  
Automatic Parking ◽  
Vehicle Path

This paper analyzes the path planning problem in the automatic parking process, and studies a path planning method for automatic parking. The grid method and the ant colony optimization are combined to find the shortest path from the parking start point to the end point. The grid method is used to model the parking environment to simulate the actual parking space of automatic parking; then this paper makes some improvements to the basic ant colony optimization, finds the destination by setting the ants’ movement rules in the grid, and finds the shortest path after N iterations; since the optimal path found is a polyline, it will increase the difficulty of controlling vehicle path tracking and affect the accuracy of vehicle path tracking. The bezier curve is used to generate a smooth path suitable for vehicle walking. Finally, through matlab simulation, the obstacles in the environment are simulated, and the parking trajectory is obtained. The results show that the path planning method proposed in this paper is feasible.

scholarly journals RimJump: Edge-based Shortest Path Planning for a 2D Map

Robotica ◽  
2018 ◽  
Vol 37 (4) ◽  
pp. 641-655 ◽  
Author(s):  
Zhuo Yao ◽  
Weimin Zhang ◽  
Yongliang Shi ◽  
Mingzhu Li ◽  
Zhenshuo Liang ◽  
...  
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Planning Method ◽  
Time Cost ◽  
Map Scale ◽  
Edge Based

SummaryPath planning under 2D map is a key issue in robot applications. However, most related algorithms rely on point-by-point traversal. This causes them usually cannot find the strict shortest path, and their time cost increases dramatically as the map scale increases. So we proposed RimJump to solve the above problem, and it is a new path planning method that generates the strict shortest path for a 2D map. RimJump selects points on the edge of barriers to form the strict shortest path. Simulation and experimentation prove that RimJump meets the expected requirements.

Neural Network Based Control System for Robots Group Operating in 2-d Uncertain Environment

2020 ◽  
Vol 21 (8) ◽  
pp. 470-479
Author(s):  
A. R. Gaiduk ◽  
O. V. Martjanov ◽  
M. Yu. Medvedev ◽  
V. Kh. Pshikhopov ◽  
N. Hamdan ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Control System ◽  
Path Planning ◽  
Shortest Path ◽  
Optimal Path ◽  
Type A ◽  
Planning Method ◽  
Target Point ◽  
Optimal Path Planning

This study is devoted to development of a neural network based control system of robots group. The control system performs estimation of an environment state, searching the optimal path planning method, path planning, and changing the trajectories on via the robots interaction. The deep learning neural networks implements the optimal path planning method, and path planning of the robots. The first neural network classifies the environment into two types. For the first type a method of the shortest path planning is used. For the second type a method of the most safety path planning is used. Estimation of the path planning algorithm is based on the multi-objective criteria. The criterion includes the time of movement to the target point, path length, and minimal distance from the robot to obstacles. A new hybrid learning algorithm of the neural network is proposed. The algorithm includes elements of both a supervised learning as well as an unsupervised learning. The second neural network plans the shortest path. The third neural network plans the most safety path. To train the second and third networks a supervised algorithm is developed. The second and third networks do not plan a whole path of the robot. The outputs of these neural networks are the direction of the robot’s movement in the step k. Thus the recalculation of the whole path of the robot is not performed every step in a dynamical environment. Likewise in this paper algorithm of the robots formation for unmapped obstructed environment is developed. The results of simulation and experiments are presented.

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