scholarly journals Real-Time Obstacle Avoidance for a Swarm of Autonomous Mobile Robots

10.5772/58478 ◽  
2014 ◽  
Vol 11 (4) ◽  
pp. 67 ◽  
Author(s):  
Ramdane Hedjar ◽  
Messaoud Bounkhel
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Autonomous Mobile Robots

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.

Vision-based smooth obstacle avoidance motion trajectory generation for autonomous mobile robots using Bézier curves

2016 ◽  
Vol 231 (3) ◽  
pp. 541-554 ◽  
Author(s):  
Kenneth Renny Simba ◽  
Naoki Uchiyama ◽  
Mohammad Aldibaja ◽  
Shigenori Sano
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Optimal Path ◽  
Trajectory Generation ◽  
Computation Time ◽  
Autonomous Mobile Robots ◽  
Bezier Curves ◽  
Bézier Curves ◽  
Time Motion

This paper proposes an obstacle avoidance trajectory generation method that provides a smooth trajectory in real time. The trajectory is generated from an environmental top-view image, where a fisheye lens is used to capture a wide area at low height. Corners of the obstacles are detected and corrected using the log-polar transform and are used to generate a simple configuration space that reduces the computation time. An optimal path is computed by using the A[Formula: see text] algorithm and replaced by a smooth trajectory generated based on piecewise quintic Bézier curves. Based on the established goal and visual information, a method for generating the first and second derivatives at the start and end points of each Bézier segment is proposed to generate a continuous curvature trajectory. The method is simple and easy to implement and has an average computation time of 1.17s on a PC (CPU: 1.4 GHz) for a workspace containing five to six obstacles. Experimental results verify that the proposed method is effective for real-time motion planning of autonomous mobile robots.

Real-time Path Adaptation for Sweeping by Autonomous Mobile Robots

1998 ◽  
pp. 299-308
Author(s):  
Daisuke Kurabayashi ◽  
Tamio Arai ◽  
Kanji Iwase ◽  
Jun Ota ◽  
Hajime Asama ◽  
...  
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Autonomous Mobile Robots ◽  
Time Path

scholarly journals 2D Lidar-Based SLAM and Path Planning for Indoor Rescue Using Mobile Robots

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xuexi Zhang ◽  
Jiajun Lai ◽  
Dongliang Xu ◽  
Huaijun Li ◽  
Minyue Fu
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Basic System ◽  
Rescue Robot ◽  
Planning Algorithm ◽  
Local Path ◽  
Slam Algorithm ◽  
Path Planning Algorithm

As the basic system of the rescue robot, the SLAM system largely determines whether the rescue robot can complete the rescue mission. Although the current 2D Lidar-based SLAM algorithm, including its application in indoor rescue environment, has achieved much success, the evaluation of SLAM algorithms combined with path planning for indoor rescue has rarely been studied. This paper studies mapping and path planning for mobile robots in an indoor rescue environment. Combined with path planning algorithm, this paper analyzes the applicability of three SLAM algorithms (GMapping algorithm, Hector-SLAM algorithm, and Cartographer algorithm) in indoor rescue environment. Real-time path planning is studied to test the mapping results. To balance path optimality and obstacle avoidance, A ∗ algorithm is used for global path planning, and DWA algorithm is adopted for local path planning. Experimental results validate the SLAM and path planning algorithms in simulated, emulated, and competition rescue environments, respectively. Finally, the results of this paper may facilitate researchers quickly and clearly selecting appropriate algorithms to build SLAM systems according to their own demands.

Sign in / Sign up

Export Citation Format

Share Document