Simultaneous Path Planning and Tracking Control in Automated Obstacle Avoidance via Feedback Control Simulation Framework

2017 ◽  
Vol 2017.26 (0) ◽  
pp. 2107
Author(s):  
Tetsuya EHIRA ◽  
Pongsathorn Raksincharoensak ◽  
Yasutaka TAGAWA
Keyword(s):  
Feedback Control ◽  
Path Planning ◽  
Obstacle Avoidance ◽  
Tracking Control ◽  
Simulation Framework ◽  
Control Simulation

Path planning and robust fuzzy output-feedback control for unmanned ground vehicles with obstacle avoidance

2020 ◽  
pp. 095440702097831
Author(s):  
Yimin Chen ◽  
Chuan Hu ◽  
Yechen Qin ◽  
Mingjun Li ◽  
Xiaolin Song
Keyword(s):  
Feedback Control ◽  
Path Planning ◽  
Obstacle Avoidance ◽  
Output Feedback ◽  
Output Feedback Control ◽  
Unmanned Ground Vehicles ◽  
Ground Vehicles ◽  
Velocity Signal ◽  
Moving Obstacles ◽  
Avoidance Strategy

Obstacle avoidance strategy is important to ensure the driving safety of unmanned ground vehicles. In the presence of static and moving obstacles, it is challenging for the unmanned ground vehicles to plan and track the collision-free paths. This paper proposes an obstacle avoidance strategy consists of the path planning and the robust fuzzy output-feedback control. A path planner is formed to generate the collision-free paths that avoid static and moving obstacles. The quintic polynomial curves are employed for path generation considering computational efficiency and ride comfort. Then, a robust fuzzy output-feedback controller is designed to track the planned paths. The Takagi–Sugeno (T–S) fuzzy modeling technique is utilized to handle the system variables when forming the vehicle dynamic model. The robust output-feedback control approach is used to track the planned paths without using the lateral velocity signal. The proposed obstacle avoidance strategy is validated in CarSim® simulations. The simulation results show the unmanned ground vehicle can avoid the static and moving obstacles by applying the designed path planning and robust fuzzy output-feedback control approaches.

scholarly journals Tracking Control for Quad-Rotor Using Velocity Field and Obstacle Avoidance Based on Hydrodynamics

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 233
Author(s):  
Julián Rascón-Enríquez ◽  
Luis Arturo García-Delgado ◽  
José R. Noriega ◽  
Alejandro García-Juárez ◽  
Eduardo S. Espinoza
Keyword(s):  
Velocity Field ◽  
Path Planning ◽  
Obstacle Avoidance ◽  
Tracking Control ◽  
Numerical Results ◽  
Recursive Method ◽  
Field Technique ◽  
Navigation Control ◽  
Total Velocity

In this work, the problem of navigation control of a quad-rotor, which includes path planning (to a desired trajectory with obstacle avoidance) and tracking control, is addressed. Path planning is achieved by means of the velocity field technique, since this method generates smooth trajectories that are suitable for this kind of vehicles. We propose a recursive method for the composition of the total velocity reference. In order to achieve a good tracking of the generated references, a saturated controller is used, namely, nested saturation. It is demonstrated that the velocity reference can be tracked with a reduction in the order of the controller, from four to three saturators, which simplifies the implementation. Numerical results show that a correct tracking could be guaranteed.

scholarly journals Different Synchronization Schemes for Chaotic Rikitake Systems

2013 ◽  
Vol 18 (2) ◽  
pp. 383-393
Author(s):  
M. Ali Khan
Keyword(s):  
Feedback Control ◽  
Tracking Control ◽  
Chaos Synchronization ◽  
Chaotic Systems ◽  
Control Simulation ◽  
Simulation Results

This paper presents the chaos synchronization by designing a different type of controllers. Firstly, we propose the synchronization of bi-directional coupled chaotic Rikitake systems via hybrid feedback control. Secondly, we study the synchronization of unidirectionally coupled Rikitake systems using hybrid feedback control. Lastly, we investigate the synchronization of unidirectionally coupled Rikitake chaotic systems using tracking control. Comparing all the results, finally, we conclude that tracking control is more effective than feedback control. Simulation results are presented to show the efficiency of synchronization schemes.

scholarly journals Development of an Improved Rapidly Exploring Random Trees Algorithm for Static Obstacle Avoidance in Autonomous Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2244
Author(s):  
S. M. Yang ◽  
Y. A. Lin
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Random Trees ◽  
Average Deviation ◽  
Lane Changes ◽  
Path Smoothing ◽  
Rapidly Exploring Random Trees

Safe path planning for obstacle avoidance in autonomous vehicles has been developed. Based on the Rapidly Exploring Random Trees (RRT) algorithm, an improved algorithm integrating path pruning, smoothing, and optimization with geometric collision detection is shown to improve planning efficiency. Path pruning, a prerequisite to path smoothing, is performed to remove the redundant points generated by the random trees for a new path, without colliding with the obstacles. Path smoothing is performed to modify the path so that it becomes continuously differentiable with curvature implementable by the vehicle. Optimization is performed to select a “near”-optimal path of the shortest distance among the feasible paths for motion efficiency. In the experimental verification, both a pure pursuit steering controller and a proportional–integral speed controller are applied to keep an autonomous vehicle tracking the planned path predicted by the improved RRT algorithm. It is shown that the vehicle can successfully track the path efficiently and reach the destination safely, with an average tracking control deviation of 5.2% of the vehicle width. The path planning is also applied to lane changes, and the average deviation from the lane during and after lane changes remains within 8.3% of the vehicle width.

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