A Novel Path Planning for Mobile Robots Using Modified Particle Swarm Optimizer

Lei, Kaiyou; Qiu, Yuhui; He, Yi

doi:10.1109/isscaa.2006.1627488

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…Lei et al employed a modified method of particle swarm optimization (PSO) to plan a robot path [2]. Du et al proposed a novel method by combining an improved Dijkstra algorithm with PSO to evaluate a global path of a mobile robot [3].…”

Section: Related Workmentioning

confidence: 99%

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Local robot path planning with predicting band trajectories of obstacles

Gong

Geng

2011

2011 Seventh International Conference on Natural Computation

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we study the problem of robot path planning in an environment with dynamic obstacles and present a method of local robot path planning with the prediction of the trajectory of an obstacle being a band. First, the time to sample information of an obstacle is determined according to its position within the vision of the robot and the trajectory of the obstacle is predicted based on information above. Different from traditional methods, the predicted trajectory is not a curve, but a band; and then the risk of collision between the robot and the obstacle is evaluated based on the predicted trajectory; finally, for the case of their collision, a mathematical model of local robot path planning is formulated and particle swarm optimization is employed to solve it. We analyze the method above theoretically and conduct simulations. The results confirm that our method decreases the probability of collision between the robot and the obstacle greatly.

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Section: Related Workmentioning

confidence: 99%

“…We can obtain that the value of 1 o v is approximate to 2.36 by equation (1) and that of 1 gap t equal to 4.12 by equation (2). And the distance between the robot and the obstacle decreases, so the position of the obstacle needs to be sampled, listed as TableⅠ.…”

Section: A Scenario 1: Only One Obstacle Appears At the Same Timementioning

confidence: 99%

Local robot path planning with predicting band trajectories of obstacles

Gong

Geng

2011

2011 Seventh International Conference on Natural Computation

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Mobile robot path planning using Ant Colony Optimization

Rashid

Perumal

Elamvazuthi

et al. 2016

2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA)

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Path planning method for robots in complex ground environment based on cultural algorithm

Guo

Yang

Cheng

2009

Proceedings of the First ACM/SIGEVO Summit on Genetic and Evolutionary Computation

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In complex ground environment, different regions have different road conditions. Path planning for robots in such environment is an open problem, which lacks effective methods. A novel global path planning method based on common sense and evolution knowledge is proposed by adopting dual evolution structure in culture algorithms. Common sense describes ground information and feasibility of environment, which is used to evaluate and select the paths. Evolution knowledge describes the angle relationship between the path and the obstacles, or the common segments of paths, which is used to judge and repair infeasible individuals. Taken two types of environments with different obstacles and road conditions as examples, simulation results indicate that the algorithm can effectively solve path planning problem in complex ground environment and decrease the computation complexity for judgment and repair of infeasible individuals. It also can improve the convergence speed and have better computation stability.

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A Novel Path Planning for Mobile Robots Using Modified Particle Swarm Optimizer

Cited by 7 publications

References 8 publications

Local robot path planning with predicting band trajectories of obstacles

Local robot path planning with predicting band trajectories of obstacles

Mobile robot path planning using Ant Colony Optimization

Path planning method for robots in complex ground environment based on cultural algorithm

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