Researches on the Robot Obstacle Avoidance Based on Fuzzy Control

2014 ◽  
Vol 686 ◽  
pp. 101-104
Author(s):  
Jin Yao
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Computer Technology ◽  
Control Algorithm ◽  
Biological Behavior ◽  
Sensor Technology ◽  
Covered Area ◽  
Local Path ◽  
Fuzzy Control Algorithm

With the continuous development of modern sensor technology, coupled with the integration of artificial intelligence and a variety of emerging computer technology, it makes robots more intelligent and diverse. So the ability of the robot to complete the task is also valued and widely used. In this paper, the whole covered area of the local path planning uses a fuzzy control algorithm, which uses the robustness and an action of perception based on the biological behavior of the fuzzy control algorithm combined with itself. For obstacle avoidance system of mobile robots, we put forward the avoidance strategy of fully contacting the obstacles. And we have conducted a deep study about the theory and implementation methods.

Space robot motion path planning based on fuzzy control algorithm

2021 ◽  
pp. 1-8
Author(s):  
Baoyu Shi ◽  
Hongtao Wu
Keyword(s):  
Path Planning ◽  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Space Robot ◽  
Robot Motion ◽  
Robot Path Planning ◽  
Behavior Based ◽  
Fuzzy Control Algorithm ◽  
Robot Path

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.

scholarly journals Artificial Intelligence Based Sensor Network Congestion Fuzzy Control Algorithm

2021 ◽  
Vol 2074 (1) ◽  
pp. 012030
Author(s):  
Jing Luo ◽  
Xiaoxu Xiao ◽  
Rongxia Wang
Keyword(s):  
Artificial Intelligence ◽  
Sensor Networks ◽  
Fuzzy Control ◽  
Sensor Network ◽  
Control Algorithm ◽  
Large Scale ◽  
Cluster Head ◽  
Residual Energy ◽  
Congestion Control Algorithm ◽  
Fuzzy Control Algorithm

Abstract The topology control of sensor sensor network was studied based on fuzzy control algorithm. Aiming at the dynamic changes of the topology of large-scale and heterogeneous artificial intelligence sensor networks and the incomplete information between nodes, a smart network-based congestion control algorithm for sensor networks was proposed and the performance of fuzzy control algorithms was analyzed. Based on this, a fuzzy control algorithm was designed. The algorithm fully considered the residual energy of nodes and the distribution of nodes in the network. Therefore, the reasonable election of the cluster head can be realized through the game between nodes, which effectively avoided energy holes, made the network energy consumption more uniform, prolonged the network life cycle, and optimized the network topology.

Fuzzy Control for the Obstacle Avoidance of a Quadrotor UAV

2015 ◽  
Vol 775 ◽  
pp. 307-313 ◽  
Author(s):  
Zi Mu Wen ◽  
Shu Dao Zhou ◽  
Min Wang
Keyword(s):  
Fuzzy Control ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Ultrasonic Sensor ◽  
Practical Application ◽  
Ultrasonic Sensors ◽  
Quadrotor Uav ◽  
Simulation Results ◽  
Fuzzy Control Algorithm

To solve the presence of the phantom phenomenon when single ultrasonic sensor detects obstacles, this paper proposes a multi-ultrasonic sensors design using grouping cycle emission. Using the fuzzy control algorithm in the obstacle avoidance simulation, the quadrotorflies through an unknown environment. The simulation results show that the algorithm can meet the requirements of the quadrotor obstacle avoidance , and have the characteristics of real-time and accuracy , provide the foundation for further practical application.

Fuzzy Control of an AGV Obstacle Avoidance System in Unknown Environments

2011 ◽  
Vol 63-64 ◽  
pp. 919-923
Author(s):  
Ke Wei Hu ◽  
Wei Yao ◽  
Li Huo Wang ◽  
Wei Zhang
Keyword(s):  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Gravity Method ◽  
Unknown Environment ◽  
Centre Of Gravity ◽  
Unknown Environments ◽  
Fuzzy Control Algorithm ◽  
Control Output

An avoiding obstacle fuzzy controller for AGV is presented in this paper. Multi-sensors are used to detect obstacles information. The fuzzy controller processes the distance of obstacles by using a 3×3 rule table. As to convert the fuzzy output into non-fuzzy value, Centre of Gravity Method (COG) is used to calculate an accurate control output. This fuzzy control algorithm can solve the problem of obstacle avoidance in unknown environment. And the AGV running path is smooth and the changing of speed is moderate.

Development of Dedicated Controller for HVAC

2012 ◽  
Vol 430-432 ◽  
pp. 1472-1476
Author(s):  
Jin Ming Yang ◽  
Yi Lin
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Control Strategies ◽  
Control Software ◽  
Interface Circuits ◽  
Pid Algorithm ◽  
Hardware Interface ◽  
Hvac Control ◽  
Fuzzy Control Algorithm

This article describes the development of a dedicated controller for HVAC control, and introduces the hardware interface circuits about some main chip on controller. In addition, the article also explains composition and principle about control software applied to the controller, further more points out that the fuzzy control algorithm is more reasonable than the PID algorithm for most HVAC control and dedicated control strategies play an important role for HVAC control.

Profile Measurement of a Curved Workpiece by the Fuzzy Control of Sensor Positioning

1999 ◽  
Author(s):  
Masatake Shiraishi ◽  
Gongjun Yang
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Experimental Results ◽  
Measuring System ◽  
Displacement Sensor ◽  
Profile Measurement ◽  
Laser Displacement Sensor ◽  
Inclination Angles ◽  
Fuzzy Control Algorithm ◽  
Sensor Positioning

Abstract A laser displacement sensor which has a resolution of 0.5 μm was used to determine the measurement of a curved workpiece profile in turning. This sensor is attached to a specially designed stage and is operated by three motors which are controlled by a fuzzy control algorithm. The experimental results show that the measuring system can be applied to workpieces having inclination angles of up to around 45°. The proposed measuring system has a practical measuring accuracy to within ten micrometers.

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