Modified formula for velocity and acceleration setting in Obstacle Avoidance problem

2016 ◽  
Author(s):  
Sri Wardani ◽  
Vera Halfiani ◽  
Said Munzir ◽  
Tarmizi Usman
Keyword(s):  
Obstacle Avoidance ◽  
Modified Formula ◽  
Avoidance Problem

scholarly journals Formation Control and Obstacle Avoidance Algorithm of a Multi-USV System Based on Virtual Structure and Artificial Potential Field

2021 ◽  
Vol 9 (2) ◽  
pp. 161
Author(s):  
Xun Yan ◽  
Dapeng Jiang ◽  
Runlong Miao ◽  
Yulong Li
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Formation Control ◽  
Shape Change ◽  
Artificial Potential Field ◽  
Generation Algorithm ◽  
Time Performance ◽  
Movement Ability ◽  
Window Approach ◽  
Avoidance Problem

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.

scholarly journals Autonomous Generation of the Potential Field on Obstacle Avoidance Problem.

1992 ◽  
Vol 10 (4) ◽  
pp. 510-519
Author(s):  
Shuichi YOKOYAMA ◽  
Masabumi UCHIDA ◽  
Kei FUKUSHIMA ◽  
Toshio AKINUMA
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Avoidance Problem

A Real-time Algorithm for Obstacle Avoidance of Autonomous Mobile Robots

Robotica ◽  
1992 ◽  
Vol 10 (3) ◽  
pp. 217-227 ◽  
Author(s):  
Huang Han-Pang ◽  
Lee Pei-Chien
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Time Algorithm ◽  
Autonomous Mobile Robots ◽  
Computational Time ◽  
Avoidance Problem

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.

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 ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Wave Motion ◽  
Specific Problem ◽  
Goal Pursuit ◽  
Potential Method ◽  
Self Organization ◽  
Appropriate Behavior ◽  
Group Of Units ◽  
Swarm Behavior ◽  
Avoidance Problem

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.

Multi-Robot nonlinear model predictive formation control: the obstacle avoidance problem

Robotica ◽  
2014 ◽  
Vol 34 (3) ◽  
pp. 549-567 ◽  
Author(s):  
Tiago P. Nascimento ◽  
André G. S. Conceição ◽  
António Paulo Moreira
Keyword(s):  
Obstacle Avoidance ◽  
Nonlinear Model ◽  
Formation Control ◽  
Potential Functions ◽  
Robot Systems ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Moving Obstacle ◽  
Avoidance Problem ◽  
Multi Robot

SUMMARYThis paper discusses about a proposed solution to the obstacle avoidance problem in multi-robot systems when applied to active target tracking. It is explained how a nonlinear model predictive formation control (NMPFC) previously proposed solves this problem of fixed and moving obstacle avoidance. First, an approach is presented which uses potential functions as terms of the NMPFC. These terms penalize the proximity with mates and obstacles. A strategy to avoid singularity problems with the potential functions using a modified A* path planning algorithm was then introduced. Results with simulations and experiments with real robots are presented and discussed demonstrating the efficiency of the proposed approach.

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