Artificial Immune System Based Path Planning of Mobile Robot

Das, Pradipta Kumar; Pradhan, Sarthak; Patro, S. N.; Balabantaray, Bunil Kumar

doi:10.1007/978-3-642-25507-6_17

Cited by 27 publications

(14 citation statements)

References 5 publications

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“…Nonetheless, as shown in the Fig. 13, the cost related to the method developed in Das et al 8 is equal to 0.2098, while the cost related to the presented method equals to 0.1522, which is 27.45% better than results of Das et al 8…”

Section: Parametermentioning

confidence: 70%

“…The robot's parameters are given in Table IX. All results are compared with the method developed in Das et al, 8 which is based on optimal control. The starting configuration is[X 0 , Y 0,0 , θ r0 , θ l0 , θ 10 , θ 20 ,θ r0 ,θ l0 ,θ 10 ,θ 20 ] = 0, 0, 0, 0, 0, π 2 − 0.1, −π + 0.1, 0, 0, 0, 0 , and the end configuration is…”

Section: Path Planning Of Non-holonomic Mobile Manipulator With 5-dofmentioning

confidence: 99%

“…Ching-Chih et al 6 presented a parallel elite genetic algorithm for path planning of mobile robots in cluttered environments. More recently, path planning of mobile robots using artificial immune system (AIS) is studied; 7,8 but only the kinematic model of mobile robot is considered. None of the previous works consider dynamic equations, large-scale systems, mobile manipulators, and wavelet mutation.…”

Section: Introductionmentioning

confidence: 99%

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Immune–wavelet optimization for path planning of large-scale robots

et al. 2013

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SUMMARYIn this paper an optimal path planning method based on a new evolutionary algorithm is presented for higher order robotic systems. It is a combination of immune system and wavelet mutation. By increasing the system's dimensions, the complexity of algorithm grows linearly. The obtained results have been compared with other optimal path producing algorithms, and its excellence in terms of optimality has been proved. Strengths of this method are simplicity in large-scale path planning, being free of most of the common deadlocks in usual method, and ability to obtain more optimized results than other similar methods. The effectiveness of this approach on simulation case studies for a three-link planar robot and 5 degrees of freedom mobile manipulators as well as an experiment for a mobile robot called K-joniour is shown.

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Section: Parametermentioning

confidence: 70%

Section: Path Planning Of Non-holonomic Mobile Manipulator With 5-dofmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Immune–wavelet optimization for path planning of large-scale robots

et al. 2013

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“…For the path planning of a single robot, Reference [7] created a robot navigation system that presented a path generation method within a maze of arbitrary complexity and optimized the generated path with the appropriate boundary conditions. An immunity algorithm is proposed by [8], in which the robot could perform its task through optimal path planning and minimal rotation angle efficiency. Traditional and heuristic approaches to path planning were proposed, such as the potential field method and A* algorithm, as seen in papers [9,10].…”

Section: Introductionmentioning

confidence: 99%

A Path Planning Strategy for Multi-Robot Moving with Path-Priority Order Based on a Generalized Voronoi Diagram

2021

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This paper proposes a new path planning strategy called the navigation strategy with path priority (NSPP) for multiple robots moving in a large flat space. In the space, there may be some static or/and dynamic obstacles. Suppose we have the path-priority order for each robot, then this article aims to find an efficient path for each robot from its starting point to its target point without any collision. Here, a generalized Voronoi diagram (GVD) is used to perform the map division based on each robot’s path-priority order, and the proposed NSPP is used to do the path planning for the robots in the space. This NSPP can be applied to any number of robots. At last, there are several simulations with a different number of robots in a circular or rectangular space to be shown that the proposed method can complete the task effectively and has better performance in average trajectory length than those by using the benchmark methods of the shortest distance algorithm (SDA) and reciprocal orientation algorithm (ROA).

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“…Das. et al [9]. The mobile robot based on the algorithm can effectively avoid obstacles and get out from the "dead zone", and then completes the path planning task.…”

Section: Introductionmentioning

confidence: 99%

Service Robots Adaptive Mutual-coupled Immune Network Planning Algorithm Research Based on the Distance-weighted

Chen¹

2018

JCP

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In order to further improve efficiency and accuracy of the multi-service robot path planning in a complex and uncertain environment, based on the mutual-coupled immune network planning algorithm, an improved measurement algorithm was proposed. According to the antigen information of obstacles and the target, situation-oriented and goal-oriented coupling immune network are defined respectively and the weight coefficient is used to control their roles in the overall behavior. In order to further improve the planning performance of the robot, weight coefficient is defined dynamically according to the distance of the robot apart from the obstacles and the target. Thus we are able to optimize the robot's behavior by choosing the obstacle-avoidance behavior or the tend-to-target behavior in real time. The test results in the static multi-obstacle environment indicate that the algorithm proposed in this paper is more effective than other algorithms in literature, both in the aspects of length and smoothness, which verifies the ability of the algorithm to improve the efficiency and precision of the path planning. And the multi-robot can successfully avoid dynamic obstacles and achieve the targeting result according to the test results in the complex and uncertainty environment, which verifies its flexibility and robustness.

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Artificial Immune System Based Path Planning of Mobile Robot

Cited by 27 publications

References 5 publications

Immune–wavelet optimization for path planning of large-scale robots

Immune–wavelet optimization for path planning of large-scale robots

A Path Planning Strategy for Multi-Robot Moving with Path-Priority Order Based on a Generalized Voronoi Diagram

Service Robots Adaptive Mutual-coupled Immune Network Planning Algorithm Research Based on the Distance-weighted

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