An Improved VFF Approach for Robot Path Planning in Unknown and Dynamic Environments

Ni, Jianjun; Wu, Wenbo; Shen, Jinrong; Fan, Xiaopeng

doi:10.1155/2014/461237

Cited by 26 publications

(12 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, a fuzzy control module was added to deal with the problem of obstacle avoidance in dynamic environments. Due to the local minimum problem and the higher computational complexity, the path could not reach optimality [7].…”

Section: Related Research Workmentioning

confidence: 99%

Interactive Heuristic D* Path Planning Solution Based on PSO for Two-Link Robotic Arm in Dynamic Environment

Raheem¹,

Hameed²

2019

WJET

View full text Add to dashboard Cite

This paper is devoted to find an intelligent and safe path for two-link robotic arm in dynamic environment. This paper focuses on computational part of motion planning in completely changing dynamic environment at every motion sample domains, since the local minima and sharp edges are the most common problems in all path planning algorithms. In addition, finding a path solution in a dynamic environment represents a challenge for the robotics researchers, so in this paper, a proposed mixing approach was suggested to overcome all these obstructions. The proposed approach methodology for obtaining robot interactive path planning solution in known dynamic environment utilizes the use of modified heuristic D-star (D*) algorithm based on the full free Cartesian space analysis at each motion sample with the Particle Swarm Optimization (PSO) technique. Also, a modification on the D* algorithm has been done to match the dynamic environment requirements by adding stop and return backward cases which is not included in the original D* algorithm theory. The resultant interactive path solution was computed by taking into consideration the time and position changes of the moving obstacles. Furthermore, to insure the enhancement of the final path length optimality, the PSO technique was used. The simulation results are given to show the effectiveness of the proposed method.

show abstract

Section: Related Research Workmentioning

confidence: 99%

Interactive Heuristic D* Path Planning Solution Based on PSO for Two-Link Robotic Arm in Dynamic Environment

Raheem¹,

Hameed²

2019

WJET

View full text Add to dashboard Cite

show abstract

“…pos ୧୨ ୲ାଵ ൌ pos ୧୨ ୲ vel ୧୨ ୲ାଵ … (9) Where ܿ ଵ and ܿ ଶ are the cognitive coefficients (ܿ ଵ +ܿ ଶ <=4), and ‫ݎ‬ ଵ, and ‫ݎ‬ ଶ, are random real numbers between [0, 1], the inertia weight ‫ݓ‬ controls the particle momentum [16][17].…”

Section: Particle Swarm Optimization Technique Theory (Pso)mentioning

confidence: 99%

“…Figure (15) represents the new path of D* based on PSO. The joint angles and change in angles based on PSO path are shown in figure (16) and (17) respectively. At first, the D* algorithm is applied to find the shortest and best path then the Particle Swarm Optimization method is used to enhance the final path by removing the sharp edges as clearly shown in results figures of the first and the second environment till finding optimal path.…”

Section: Second Environmentmentioning

confidence: 99%

“…The result clearly proves the advantage of using the proposed mixed approach as shown in table (2). In comparison with other path planning algorithms like artificial potential field (APF) [2,17], the heuristic D* is more suitable for the dynamic environment because of its behavior in saving cost and gives safe and better path length cost function. In addition, the most important issue is the heuristic methods does not suffer from the local minima problem that appears mainly in APF path planning approaches.…”

Section: Second Environmentmentioning

confidence: 99%

See 1 more Smart Citation

Heuristic D* Algorithm Based on Particle Swarm Optimization for Path Planning of Two-Link Robot Arm in Dynamic Environment

Raheem¹,

Hameed²

2019

alkej

View full text Add to dashboard Cite

Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved. In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO) technique. Moreover, this work focuses on computational part of motion planning in completely changing dynamic environment at every motion sample domains. Since the environment type that discussed here is a known dynamic environment, the solution approach can be off-line. The main advantage of the off-line planning is that a global optimal path solution is always obtained, which is able to overcome all the difficulties caused by the dynamic behavior of the obstacles. A mixing approach of robot path planning using the heuristic method D* algorithm based on optimization technique is used. The heuristic D* method is chosen for finding the shortest path. Furthermore, to insure the path length optimality and for enhancing the final path, PSO technique has been utilized. The robot type has been used here is the two-link robot arm which represents a more difficult case than the mobile robot. Simulation results are given to show the effectiveness of the proposed method which clearly shows a completely safe and short path.

show abstract

“…Quadruped robot has good structural stability [1,2], dynamic compensation system, and the carrying capacity [3][4][5]. Quadruped robot has flexible adaptability in unstructured complex environments and also can walk and complete tasks such as search and rescue [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Guaranteed Cost Nonfragile Robust Controller for Walking Simulation of Quadruped Search Robot on a Slope of VRML Model

Wang

Zhang

2014

Advances in Mechanical Engineering

View full text Add to dashboard Cite

The problem of walking simulation for the quadruped search robot on a slope is described as an uncertainty system. In order to create the virtual ramp road environment, VRML modeling language is used to build a real environment, which is a 3D terrain scene in Matlab platform. According to the VRML model structure of the quadruped search robot, a guaranteed cost nonfragile robust controller is designed for ramp road walking simulation. The constraint inequation is transformed into a strict linear inequality by using two equalities; the controller and the guaranteed cost upper bound are given based on the solutions of the linear matrix inequality. And the approaches of designing the controller are given in terms of linear matrix inequalities. The walking stability of quadruped search robot is observed using the VRML model established with the change of gravity curve. Simulation results show that the gravity displacement curve of the robot is smooth. The results given by linear matrix inequalities indicate that the proposed guaranteed cost controller is correct and effective.

show abstract

An Improved VFF Approach for Robot Path Planning in Unknown and Dynamic Environments

Cited by 26 publications

References 29 publications

Interactive Heuristic D* Path Planning Solution Based on PSO for Two-Link Robotic Arm in Dynamic Environment

Interactive Heuristic D* Path Planning Solution Based on PSO for Two-Link Robotic Arm in Dynamic Environment

Heuristic D* Algorithm Based on Particle Swarm Optimization for Path Planning of Two-Link Robot Arm in Dynamic Environment

Guaranteed Cost Nonfragile Robust Controller for Walking Simulation of Quadruped Search Robot on a Slope of VRML Model

Contact Info

Product

Resources

About