scholarly journals A New Efficient Obstacle Avoidance Control Method for Cars Based on Big Data and Just-in-Time Modeling

2018 ◽  
Vol 06 (11) ◽  
pp. 12-22
Author(s):  
Tatsuya Kai
Keyword(s):  
Big Data ◽  
Obstacle Avoidance ◽  
Control Method ◽  
Just In Time ◽  
Time Modeling ◽  
Avoidance Control

Obstacle Avoidance Control Method of Mobile Robot Motion

2013 ◽  
Vol 443 ◽  
pp. 119-122
Author(s):  
Bin Zhou ◽  
Jin Fa Qian
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Control Method ◽  
Intelligent System ◽  
Development Trend ◽  
Working Environment ◽  
Intelligent Algorithm ◽  
Control Field ◽  
Avoidance Control ◽  
The Development Trend

Mobile robot is an intelligent system which can move freely and is scheduled to complete the task in the working environment. Obstacle avoidance of mobile robot is the research hotspot in the control field of the mobile robot. The mobile robot obstacle avoidance methods are classified, including the traditional algorithms and the intelligent algorithms. This paper summarizes the intelligent algorithm in the mobile robot obstacle avoidance technique in the present situation, and the intelligent algorithm which is the most researched in the current. Finally, this paper prospects the development trend of intelligent obstacle avoidance of the robot.

Emergency Obstacle Avoidance Control Method Based on Driver Steering Intention Recognition for Steer-by-Wire Vehicle

2013 ◽  
Vol 694-697 ◽  
pp. 2738-2741
Author(s):  
Lei He ◽  
Hai Ou Xiang ◽  
Dong Xue Chen ◽  
Chang Fu Zong
Keyword(s):  
Obstacle Avoidance ◽  
Driving Simulator ◽  
Response Rate ◽  
Control Method ◽  
Recognition Accuracy ◽  
Recognition Method ◽  
Intention Recognition ◽  
Steer By Wire ◽  
Avoidance Control ◽  
Stability Time

This paper proposes an emergency obstacle avoidance control method based on driver steering intention recognition for steer-by-wire vehicle in order to solve the problem that the response rate and stability time are unsatisfactory. The paper focuses on the method to recognize driver steering intention, and builds a driver steering behavior model by using the multidimensional Gauss HMM theory, optimizes the model by using the Baum-Welch algorithm and conducts real-time verification on steering intention recognition by means of LabVIEW and driving simulator. The results indicate that the driver steering intention recognition method has higher recognition accuracy and can help to realize emergency obstacle avoidance control effectively for steer-by-wire vehicle.

scholarly journals Path Following Based on Waypoints and Real-Time Obstacle Avoidance Control of an Autonomous Underwater Vehicle

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 795 ◽  
Author(s):  
Xuliang Yao ◽  
Xiaowei Wang ◽  
Feng Wang ◽  
Le Zhang
Keyword(s):  
Real Time ◽  
Obstacle Avoidance ◽  
Autonomous Underwater Vehicle ◽  
Control Method ◽  
Path Following ◽  
Underwater Vehicle ◽  
System Stability ◽  
Guidance Law ◽  
Angular Velocities ◽  
Avoidance Control

This paper studies three-dimensional (3D) straight line path following and obstacle avoidance control for an underactuated autonomous underwater vehicle (AUV) without lateral and vertical driving forces. Firstly, the expected angular velocities are designed by using two different methods in the kinematic controller. The first one is a traditional method based on Line-of-sight (LOS) guidance law, and the second one is an improved method based on model predictive control (MPC). At the same time, a penalty item is designed by using the obstacle information detected by onboard sensors, which can realize the real-time obstacle avoidance of the unknown obstacle. Then, in order to overcome the uncertainty of the dynamics model and the saturation of actual control input, the dynamic controller is designed by using sliding mode control (SMC) technology. Finally, in the simulation experiment, the performance of the improved control method is verified by comparison with two traditional control methods based on LOS guidance law. Since the constraint of an AUV’s angular velocities are considered in MPC, simulation results show that the improved control method uses MPC, and SMC not only improves the tracking quality of the AUV when switching paths near the waypoints and realizes real-time obstacle avoidance but also effectively reduces the mean square error (MSE) and saturation rate of the rudder angle. Therefore, this control method is more conducive to the system stability and saves energy.

scholarly journals Hierarchical fuzzy obstacle avoidance control of omnidirectional mobile robot for substation inspection

2021 ◽  
Vol 233 ◽  
pp. 04003
Author(s):  
Li Ma
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
High Speed ◽  
Control Method ◽  
Path Model ◽  
Set Design ◽  
Avoidance Control ◽  
Control Set ◽  
Fast Control ◽  
Control Quantity

There are some limitations in the practical application of robot obstacle avoidance control methods. In order to realize the high-speed planning and obstacle avoidance processing of mobile robot, the path model, inspection route and path obstacles of the robot must be fully considered. Through feature extraction, the reasonable planning of substation inspection obstacle avoidance route is realized, and the control quantity set satisfying substation inspection is given. The hierarchical fuzzy obstacle avoidance control method of mobile robot is realized by using the optimal control set design. The simulation results show that the control method can solve various complex problems when the robot contour collides with obstacles, and can realize safe and fast control. The flexibility and robustness of obstacle avoidance are improved, and the motion state and speed of obstacles are also improved.

scholarly journals UAV formation obstacle avoidance control method based on artificial potential field and consistency

2021 ◽  
Vol 2083 (4) ◽  
pp. 042029
Author(s):  
Boyu Wei
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Formation Control ◽  
Control Method ◽  
Artificial Potential Field ◽  
Time Varying ◽  
Complex Environments ◽  
Control Scheme ◽  
Avoidance Control ◽  
Multi Agent

Abstract As a typical multi-agent formation, UAV formation is playing an increasingly powerful role in the civilian and military fields. Obstacle avoidance, as an important technology in controlling formation, determines the application prospects of UAVs. This paper studies the time-varying formation of UAVs with interactive topology to avoid obstacles, aiming to improve the ability of UAV formations to deal with complex environments while traveling. Firstly, a repulsive force field is reasonably introduced based on the existing control scheme, and an improved distributed time-varying formation control scheme based on artificial potential field is proposed. Then combined with the basic idea of model predictive control, an obstacle avoidance strategy in which UAV obstacle avoidance and formation shaping are carried out simultaneously is proposed. Finally, a time-varying formation simulation experiment containing four UAVs was carried out to verify the validity of the results.

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