Obstacle Avoidance Using Vibrating Potential Method (Self-Organization in a Narrow Path)

1996 ◽  
Vol 8 (4) ◽  
pp. 356-363 ◽  
Author(s):  
Hiroshi Yokoi ◽  
◽  
Takafumi Mizuno ◽  
Masatosi Takita ◽  
Yukinori Kakazu ◽  
...  

In this paper we use the vibrating potential method 2) (VPM) in an attempt to solve the obstacle avoidance problem. The paper reports swarm behavior for finding suitable avoidance that is derived from the VPM through self-organization. In the VPM, AGV consists of a group of units that has elementary sensor, action, controller, and communication functions. The communication media is through wave propagation on the vibrating potential field. The wave motion propagates from each of these units, and informs the unit's status to other units. From this wave motion, the AGVs obtain information about their environments and are thus able to choose appropriate behavior (i.e., obstacle avoidance and goal pursuit.) This system is advantageous to users because the AGVs do not require programming oriented to a specific problem. We provide illustrations in the form of computer simulations. These show AGVs as they pursue goals, avoid obstacles, and as they leave and rejoin a group.

2021 ◽  
Vol 9 (2) ◽  
pp. 161
Author(s):  
Xun Yan ◽  
Dapeng Jiang ◽  
Runlong Miao ◽  
Yulong Li

This paper proposes a formation generation algorithm and formation obstacle avoidance strategy for multiple unmanned surface vehicles (USVs). The proposed formation generation algorithm implements an approach combining a virtual structure and artificial potential field (VSAPF), which provides a high accuracy of formation shape keeping and flexibility of formation shape change. To solve the obstacle avoidance problem of the multi-USV system, an improved dynamic window approach is applied to the formation reference point, which considers the movement ability of the USV. By applying this method, the USV formation can avoid obstacles while maintaining its shape. The combination of the virtual structure and artificial potential field has the advantage of less calculations, so that it can ensure the real-time performance of the algorithm and convenience for deployment on an actual USV. Various simulation results for a group of USVs are provided to demonstrate the effectiveness of the proposed algorithms.


1992 ◽  
Vol 10 (4) ◽  
pp. 510-519
Author(s):  
Shuichi YOKOYAMA ◽  
Masabumi UCHIDA ◽  
Kei FUKUSHIMA ◽  
Toshio AKINUMA

Robotica ◽  
1992 ◽  
Vol 10 (3) ◽  
pp. 217-227 ◽  
Author(s):  
Huang Han-Pang ◽  
Lee Pei-Chien

SUMMARYA real-time obstacle avoidance algorithm is proposed for autonomous mobile robots. The algorithm is sensor-based and consists of a H-mode and T-mode. The algorithm can deal with a complicated obstacle environment, such as multiple concave and convex obstacles. It will be shown that the algorithm is more efficient and more robust than other sensor-based algorithms. In addition, the algorithm will guarantee a solution for the obstacle avoidance problem. Since the algorithm only takes up a small computational time, it can be implemented in real time.


1993 ◽  
Vol 5 (5) ◽  
pp. 481-486 ◽  
Author(s):  
Masafumi Uchida ◽  
◽  
Syuichi Yokoyama ◽  
Hideto Ide ◽  

The potential method is superior for solving the problem of motion planning; however, it must address the problem of the real-time generation of potential field. Obstacle avoidance is a motion planning problem. In a previous study, we investigated the real-time generation of potential field. Based on parallel processing with element group, we proposed the system by Sensory Point Moving (SPM) method. As a result of computer simulation, it was confirmed that the SPM method is effective for generating an obstacle avoidance path in 2-D and a more complex working environment like a 3-D one. In this paper, we discuss the development of autonomous mobile robot for obstacle avoidance based on the SPM method.


2013 ◽  
Vol 2013.51 (0) ◽  
pp. _808-1_-_808-2_
Author(s):  
Yohei MIYAUCHI ◽  
Satoki SAWA ◽  
Maroi KODAMA ◽  
Masashi MIURA ◽  
Kazunori SAKURAMA ◽  
...  

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