Wide Range Global Path Planning for a Large Number of Networked Mobile Robots based on Generalized Voronoi Diagrams

Wang, Qi; Langerwisch, Marco; Wagner, Bernd

doi:10.3182/20131111-3-kr-2043.00007

Cited by 22 publications

(12 citation statements)

References 8 publications

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“…where ψ s = θ s + ϕ s and ϕ s represents the angle of the sensor S to the obstacle b with respect to the body of the robot. At subsequent distance readings, the distance d o = dist(b, b ) between the initial b and current b position sensor readings of an obstacle can be computed using (11). Using this kinematics, detected obstacles are analyzed to determine their collision threat levels and the required path replanning decision.…”

Section: Problem Formulation and Assumptionsmentioning

confidence: 99%

“…VD is noted for not compromising path safety by computing roadmaps which are equidistant between obstacles. Arguably, VD based path planning has attracted the attention of many researchers [6]- [11]. Based on generalized VD, electric circuit-based path planning method for multiple robot path planning was presented in [11] to address traffic jam problems.…”

Section: Introductionmentioning

confidence: 99%

“…Arguably, VD based path planning has attracted the attention of many researchers [6]- [11]. Based on generalized VD, electric circuit-based path planning method for multiple robot path planning was presented in [11] to address traffic jam problems. Moreover, a motion planning approach with VD through a line-segment map was presented in [9].…”

Section: Introductionmentioning

confidence: 99%

“…11) where (b x , b y ) and (b x , b y ) are the initial and current positions of the obstacle. With ϕ s being the orientation of the sensor S to the obstacle, the estimated sensor direction to different positions of a dynamic obstacle with respect to the robot frame can be represented as ϕ s(i) where i = {1, 2, 3, .…”

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confidence: 99%

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Mobile Robot Path Planning in Dynamic Environment Using Voronoi Diagram and Computation Geometry Technique

et al. 2019

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This paper presents a novel path planning method for mobile robots in complex and dynamic environments using Voronoi diagram (VD) and computation geometry technique (CGT) termed, VD-CGT. An algorithm to categorize moving obstacles based on their positions, velocities, distances, and directions to ascertain their collision threat level and possible replanning decision is introduced. The initial path computation is done using morphological dilation, VD, A-star, and cubic spline algorithms. Instead of considering the entire map of the environment, CGT is used to compute a small rectangular region estimated to enclose a detected collision-threat obstacle and the current position of the robot. The roadmap is computed in the geometrical shape using VD and nodes are added to the initial roadmap nodes to compute a new path for replanning. To avoid increasing time and space requirements, these nodes are discarded before subsequent replanning is done. The results indicate better path replanning performance in complex and dynamic environments in terms of success path computation rate, path cost, time, and the number of replanning computations compared with other five popular related path planning approaches. The proposed method is efficient, and it computes safe and shortest replan path to goal with low computation time requirement. Unnecessary replanning computations are avoided which aid in reducing time and distance to get to the goal. With the performance results, the proposed method is a promising method for achieving safe, less path cost, and time in path replanning computations in complex and dynamic environments.INDEX TERMS Mobile robot, motion planning, path planning, unmanned autonomous vehicles, Voronoi diagram.

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Section: Problem Formulation and Assumptionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Mobile Robot Path Planning in Dynamic Environment Using Voronoi Diagram and Computation Geometry Technique

et al. 2019

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“…The grid method can grid the working environment, and is a convenient and straightforward approach [2,15]. The Voronoi diagram generated by Delaunay triangulation [16][17][18] can order the complex obstacle environment, and is widely used in the environment modeling of mobile robots [19][20][21]. After the map is processed, the common path planning algorithm includes the D* algorithm, Genetic Algorithm (GA), Ant Colony Optimization Algorithm (ACO), and A*.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Fusion Pathfinding Algorithm Using Delaunay Triangulation and Improved A-Star for Mobile Robots

Liu

et al. 2021

IEEE Access

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Although many studies exist on mobile robot path planning, the disadvantages of complex algorithms and many path nodes in logistics warehouses and manufacturing workshops are obvious, mainly due to the inconsistency of map environment construction and pathfinding strategies. In this study, to improve the efficiency of mobile robot path planning, the Delaunay triangulation algorithm was used to process complex obstacles and generate Voronoi points as pathfinding priority nodes. The concept of the grid was used to extract obstacle edges to provide obstacle avoidance strategies for robot pathfinding. Subsequently, the search for priority and regular path nodes used the improved A-star (A*) algorithm. The dynamic fusion pathfinding algorithm (DFPA), based on Delaunay triangulation and improved A*, was designed, which realizes the path planning of mobile robots. MATLAB 2016a was used as the simulation software, to firstly verify the correctness of the DFPA, and then to compare the algorithm with other methods. The results show that under the experimental environment with the same start point, goal point, and number of obstacles, the map construction method and pathfinding strategy proposed in this paper reduce the planned path length of the mobile robot, the number of path nodes, and the cost of overall turn consumption, and increase the success rate of obtaining a path. The new dynamic map construction method and pathfinding strategy have important reference significance for processing chaotic maps, promoting intelligent navigation, and site selection planning.INDEX TERMS Delaunay triangulation, A-star algorithm, mobile robot, map modeling, path planning.

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A study on path planning optimization of mobile robots based on hybrid algorithm

Garip

Karayel

Çimen

2021

Concurrency and Computation

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The purpose of this study is to develop a novel hybrid meta‐heuristic algorithm for optimal path planning of the mobile robot. A novel hybrid algorithm based on particle swarm optimization (PSO), firefly algorithm (FA), and cuckoo search (CS) is proposed in order to improve the efficiency of algorithms and minimize the cost performance criterion in path planning. First, A MATLAB based interface was designed to easily perform all activities such as generating maps by processing the images taken from the camera, finding paths with algorithms, communicating with robots, and navigating according to path information that the robot determines with algorithms. Second, for path planning in mobile robots, the developed CS‐PSO‐FA hybrid algorithm and CS, FA, PSO algorithms were carried out both simulation and experimentally without hitting obstacles in similar working environments. In addition, various applications are performed in the various simulation environments to verify the developed CS‐PSO‐FA hybrid algorithm and the obtained results are compared. In conclusion, it is demonstrated that the path obtained with the novel hybrid CS‐PSO‐FA algorithm is shorter than CS, PSO, and FA algorithms and thus has a higher performance and the feasibility.

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Wide Range Global Path Planning for a Large Number of Networked Mobile Robots based on Generalized Voronoi Diagrams

Cited by 22 publications

References 8 publications

Mobile Robot Path Planning in Dynamic Environment Using Voronoi Diagram and Computation Geometry Technique

Mobile Robot Path Planning in Dynamic Environment Using Voronoi Diagram and Computation Geometry Technique

A Dynamic Fusion Pathfinding Algorithm Using Delaunay Triangulation and Improved A-Star for Mobile Robots

A study on path planning optimization of mobile robots based on hybrid algorithm

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