An Improved Path Planning Method Based on Artificial Potential Field for a Mobile Robot

Chen, Wenbai; Wu, Xiaotian; Lü, Yang

doi:10.1515/cait-2015-0037

Cited by 29 publications

(21 citation statements)

References 16 publications

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“…APF is a virtual force method proposed by Khatib, which designs the motion space of the robot in the surrounding environment as an abstract virtual force field [9]. The target point produces the gravitational potential field ⃗ ⃗ to the robot, calculates the negative gradient to obtain its gravitational force , the obstacle produces the repulsive potential field ⃗ ⃗ to the robot, calculates the negative gradient to obtain , and finally controls the robot movement through the resultant force [10], as shown in Fig. 2.…”

Section: Traditional Apfmentioning

confidence: 99%

Research on SLAM and Path Planning Based on ROS Robot

Li¹,

Li²,

Shi³

et al. 2020

International Conference of Control, Dynamic Systems, and Robotics

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With the development of artificial intelligence technology, human-computer interaction has become the trend of robot research, navigation robots are widely used. Navigation robots autonomous navigation in an unknown environment, including perception of the environment, autonomous positioning and dynamic obstacle avoidance, etc. Among them, Simultaneous Localization and Mapping (SLAM) and path planning are prerequisites for achieving robot intelligent navigation. Aiming at problems such as low positioning accuracy and inability to accurately sense obstacles in 3D complex environments when using lidar. Firstly, based on the data characteristics of lidar and depth camera, the projection of point cloud collected by depth camera on 2D plane and lidar point cloud are fused by Bayes formula, then build an occupied grid map of the indoor complex environment. In addition, the traditional artificial potential field (APF) is easy to fall into the local optimal solution and oscillation of the potential field, and there may be collisions in the presence of dynamic obstacles. In the face of complex dynamic environments, it is difficult to plan a complete path. The velocity factor of obstacles is added to judge the movement trend of obstacles in the APF method, and a new repulsion function is introduced to overcome the local optimal trap and avoid the problem that obstacles near the target point lead to the target unreachable. Experiments show that the fusion raster map has higher precision than the single laser radar in the establishment of grid maps. In the aspect of path planning, the improved APF method can effectively solve the stochastic dynamic obstacles, and improve the navigation efficiency of robots.

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Section: Traditional Apfmentioning

confidence: 99%

Research on SLAM and Path Planning Based on ROS Robot

Li¹,

Li²,

Shi³

et al. 2020

International Conference of Control, Dynamic Systems, and Robotics

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show abstract

“…The parameters of straight lines that most closely fit the measurements of the original sample M manifest as pronounced local maxima. However, the automatic selection of lines is beset by statistical challenges; especially, the quantification of local maxima is confounded by various noises derived from the source, sampling round-off, and other factors [18]. For this reason, direct determination of the maxima in matrix A is not a suitable strategy for evaluating an object's image rotation.…”

Section: Problem Settingmentioning

confidence: 99%

Evaluation of Two-Dimensional Angular Orientation of a Mobile Robot by a Modified Algorithm Based on Hough Transform

Aldoshkin

Tsarev

2018

Cybernetics and Information Technologies

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This paper proposes an algorithm that assesses the angular orientation of a mobile robot with respect to its referential position or a map of the surrounding space. In the framework of the suggested method, the orientation problem is converted to evaluating a dimensional rotation of the object that is abstracted as a polygon (or a closed polygonal chain). The method is based on Hough transform, which transforms the measurement space to a parametric space (in this case, a two-dimensional space [θ, r] of straight-line parameters). The Hough transform preserves the angles between the straight lines during rotation, translation, and isotropic scaling transformations. The problem of rotation assessment then becomes a one-dimensional optimization problem. The suggested algorithm inherits the Hough method’s robustness to noise.

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“…The APF is created from two sources such as the potential field between AUVs themselves, AUV and desired trajectory points. The goals of the APF are: (a) Improving the local dynamic behaviour of the AUV along the optimised paths (Xing-Jian et al 2004); (b) Reducing the number of local minimum and/or the size of their attractive wells (Chen et al 2015).…”

Section: Csa-apf Optimisationmentioning

confidence: 99%

Co-operative control of a team of autonomous underwater vehicles in an obstacle-rich environment

Das

Subudhi

Pati

2016

Journal of Marine Engineering & Technology

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This paper presents the cooperative control of a team of autonomous underwater vehicles (AUVs) in the presence of obstacles under environmental disturbance. A leader-follower formation control based on optimisation algorithms using communication topology is designed to navigate towards the target in the presence of obstacles. CLONAL selection optimisation algorithm may be employed as team controller by providing the optimal position to hierarchical control strategy for each AUV incorporating learning, memory and affinity. But unfortunately CLONAL selection optimisation algorithm fails to avoid obstacles because some of the lymphocytes become memory cells of the system. The above prematurity may be overcome by using artificial potential fields and ant colony optimisation technique combined with CLONAL selection optimisation algorithm. The efficacy of the proposed optimisation is verified through MATLAB simulation and the result confirmed the robustness and proficiency of proposed technique over CLONAL selection optimisation algorithm.

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An Improved Path Planning Method Based on Artificial Potential Field for a Mobile Robot

Cited by 29 publications

References 16 publications

Research on SLAM and Path Planning Based on ROS Robot

Research on SLAM and Path Planning Based on ROS Robot

Evaluation of Two-Dimensional Angular Orientation of a Mobile Robot by a Modified Algorithm Based on Hough Transform

Co-operative control of a team of autonomous underwater vehicles in an obstacle-rich environment

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