scholarly journals Research on obstacle avoidance method of robot manipulator based on binocular vision

2021 ◽  
Vol 1948 (1) ◽  
pp. 012107
Author(s):  
Xiaoyang Zhang ◽  
Xiaoming Guo ◽  
Zhenyu Sun
1997 ◽  
Vol 9 (6) ◽  
pp. 482-489
Author(s):  
Takahiro Tsuchiya ◽  
◽  
Ryosuke Masuda ◽  

In this paper, we discuss the sensor allocation problem in detecting obstacles in robot manipulators. The detection of obstacles in a work area is important for safety purposes and for the efficiency of robot control. Therefore, it is necessary to allocate the sensors properly on the links in a robot manipulator. Here, we propose two types of effective sensor allocation methods. One is based on the joint coordinates of the robot, and the other is based on the orthogonal work space. In addition, we show the allocation of additional sensors based on the quantitative conditions of the robot and its obstacles. The optical proximity sensor, which was developed by the authors, is used, and the proposed allocation methods are applied using a SCARA-type robot. It is proved, by experiments on obstacle avoidance control, that effective sensor allocations can be found.


2019 ◽  
Vol 12 (1) ◽  
pp. 56-65
Author(s):  
Ali N. Abdulnabi

This paper presents a collision-free path planning approaches based on Bézier curve and A-star algorithm for robot manipulator system. The main problem of this work is to finding a feasible collision path planning from initial point to final point to transport the robot arm from the preliminary to the very last within the presence of obstacles, a sequence of joint angles alongside the path have to be determined. To solve this problem several algorithms have been presented among which it can be mention such as Bug algorithms, A-Star algorithms, potential field algorithms, Bézier curve algorithm and intelligent algorithms. In this paper obstacle avoidance algorithms were proposed Bézier and A-Star algorithms, through theoretical studies and simulations with several different cases, it's found verify the effectiveness of the methods suggested. It's founded the Bézier algorithm is smoothing accurate, and effective as compare with the A-star algorithm, but A-star is near to shortest and optimal path to free collision avoidance. The time taken and the elapsed time to traverse from its starting position and to reach the goal are recorded the tabulated results show that the elapsed time with different cases to traverse from the start location to destination using A-star Algorithm is much less as compared to the time taken by the robot using Bézier Algorithm to trace the same path. The robot used was the Lab-Volt of 5DOF Servo Robot System Model 5250 (RoboCIM5250)


Robotica ◽  
1997 ◽  
Vol 15 (1) ◽  
pp. 3-10 ◽  
Author(s):  
Ziqiang Mao ◽  
T. C. Hsia

This paper investigates the neural network approach to solve the inverse kinematics problem of redundant robot manipulators in an environment with obstacles. The solution technique proposed requires only the knowledge of the robot forward kinematics functions and the neural network is trained in the inverse modeling manner. Training algorithms for both the obstacle free case and the obstacle avoidance case are developed. For the obstacle free case, sample points can be selected in the work space as training patterns for the neural network. For the obstacle avoidance case, the training algorithm is augmented with a distance penalty function. A ball-covering object modeling technique is employed to calculate the distances between the robot links and the objects in the work space. It is shown that this technique is very computationally efficient. Extensive simulation results are presented to illustrate the success of the proposed solution schemes. Experimental results performed on a PUMA 560 robot manipulator is also presented.


2021 ◽  
Vol 16 ◽  
Author(s):  
Hongxin Zhang ◽  
Jiaming Li ◽  
Rongzijun Shu ◽  
Hongyu Wang ◽  
Guangsen Li

Background: With the development of robotics, more and more robots are used in manufacturing. However, in actual work, safety accidents happen to robots from time to time. How to ensure the safe operation of robots in a limited and complex working environment is the key to improve robot technology. Therefore, it is of great significance to study the dynamic obstacle avoidance of robots in complex environment for improving the intelligence and safety of robots, and the application of human-robot collaboration. Objective: The primary purpose of this paper is to improve the traditional artificial potential field method, including he disadvantages that the improved target is inaccessible and easily plunged into local optimal solution of the drawback of the improved method, second. Secondly, the background difference method based on binocular vision and Kalman filtering algorithm, and the environmental map containing the static and dynamic obstacles is obtained. After obtaining the position information of static and dynamic obstacles, the robot arm can make good use of the improved artificial potential field method to plan its own trajectory, thus realizing the dynamic obstacle avoidance of the robot arm in complex environment. Methodology: The background difference method and the Kalman filtering algorithm based on binocular vision were introduced to track the dynamic obstacles, and the improved artificial potential field method for path planning was applied to the dynamic obstacle avoidance path planning of the manipulator. Finally, the simulation and experimental results show that under the complex environment with dynamic obstacles exist, robot arm can realize independent dynamic obstacle avoidance. Results: By using background difference method and Kalman filtering algorithm to track the target in real time, the result showed that the target could be detected and tracked well. By improving the defect that the traditional artificial potential field method is easy to fall into local optimum, the improved algorithm can well realize the dynamic obstacle avoidance of the manipulator. Conclusions: For the development requirements of the industrial robots in the future, this paper based on binocular vision, which can make the manipulator realize more intelligent industrial production activities in complex working environment, meet the needs of future industrial development, and make this technology play an important role in production activities.


2014 ◽  
Vol 530-531 ◽  
pp. 1063-1067 ◽  
Author(s):  
Wei Ji ◽  
Jun Le Li ◽  
De An Zhao ◽  
Yang Jun

To the problems of real-time obstacle avoidance path planning for apple harvesting robot manipulator in dynamic and unstructured environment, a method based on improved ant colony algorithm is presented. Firstly, Vector description is utilized to describe the area where obstacles such as branches is located as irregular polygon in free space, and MAKLINK graph is used to build up the environment space model. Then, the improved Dijkstra algorithm is used to find the initial walk path for apple harvesting robot manipulator. Finally, the improved ant colony algorithm is applied to optimize the initial path. The experiment result shows that the proposed method is simple and the robot manipulator can avoid the branches to pick the apple successfully in a relatively short time.


Sign in / Sign up

Export Citation Format

Share Document