Moving Objects in the Problem of Path Planning by Evolutionary Computation

2003 ◽  
pp. 382-387
Author(s):  
Roman Śmierzchalski ◽  
Andrzej Łebkowski
Keyword(s):  
Path Planning ◽  
Evolutionary Computation ◽  
Moving Objects

Impedance Control: An Approach to Manipulation: Part III—Applications

1985 ◽  
Vol 107 (1) ◽  
pp. 17-24 ◽  
Author(s):  
Neville Hogan
Keyword(s):  
Feedback Control ◽  
Path Planning ◽  
Control Algorithm ◽  
Moving Objects ◽  
Impedance Control ◽  
Optimization Theory ◽  
Dynamic Interaction ◽  
Unified Approach ◽  
Simplified Analysis ◽  
Unconstrained Motion

This three-part paper presents a unified approach to the control of a manipulator applicable to free motions, kinematically constrained motions, and dynamic interaction between the manipulator and its environment. In Part I the approach was developed from a consideration of the fundamental mechanics of manipulation. Part II presented techniques for implementing a desired manipulator impedance. In Part III a technique for choosing the impedance appropriate to a given application using optimization theory is presented. Based on a simplified analysis it is shown that if the task objective is to tradeoff interface forces and motion errors, the manipulator impedance should be proportional to the environmental admittance. An application of impedance control to unconstrained motion is presented. The superposition properties of nonlinear impedances are used to develop a real-time feedback control algorithm which permits a manipulator to avoid unpredictably moving objects without explicit path planning.

Hybrid obstacle avoidance system with vision and ultrasonic sensors for multi-rotor MAVs

2018 ◽  
Vol 45 (2) ◽  
pp. 227-236 ◽  
Author(s):  
Qiang Zhou ◽  
Danping Zou ◽  
Peilin Liu
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Moving Objects ◽  
Point Clouds ◽  
Ultrasonic Sensor ◽  
Content Type ◽  
Stereo Camera ◽  
3D Point Clouds ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Purpose This paper aims to develop an obstacle avoidance system for a multi-rotor micro aerial vehicle (MAV) that flies in indoor environments which usually contain transparent, texture-less or moving objects. Design/methodology/approach The system adopts a combination of a stereo camera and an ultrasonic sensor to detect obstacles and extracts three-dimensional (3D) point clouds. The obstacle map is built on a coarse global map and updated by local maps generated by the recent 3D point clouds. An efficient layered A* path planning algorithm is also proposed to address the path planning in 3D space for MAVs. Findings The authors conducted a lot of experiments in both static and dynamic scenes. The results show that the obstacle avoidance system works reliably even when transparent or texture-less obstacles are present. The layered A* path planning algorithm is much faster than the traditional 3D algorithm and makes the system response quickly when the obstacle map has been changed because of the moving objects. Research limitations/implications The limited field of view of both stereo camera and ultrasonic sensor makes the system need to change heading first before moving side to side or moving backward. But this problem could be addressed when multiple systems are mounted toward different directions on the MAV. Practical implications The developed approach could be valuable to applications in indoors. Originality/value This paper presents a robust obstacle avoidance system and a fast layered path planning algorithm that are easy to be implemented for practical systems.

scholarly journals Improved Artificial Potential Field Method Applied for AUV Path Planning

2020 ◽  
Vol 2020 ◽  
pp. 1-21 ◽  
Author(s):  
Xiaojing Fan ◽  
Yinjing Guo ◽  
Hui Liu ◽  
Bowen Wei ◽  
Wenhong Lyu
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Potential Field ◽  
Moving Objects ◽  
Dynamic Environment ◽  
Planning Method ◽  
Artificial Potential Field ◽  
Local Minima ◽  
Field Function ◽  
Time Path

With the topics related to the intelligent AUV, control and navigation have become one of the key researching fields. This paper presents a concise and reliable path planning method for AUV based on the improved APF method. AUV can make the decision on obstacle avoidance in terms of the state of itself and the motion of obstacles. The artificial potential field (APF) method has been widely applied in static real-time path planning. In this study, we present the improved APF method to solve some inherent shortcomings, such as the local minima and the inaccessibility of the target. A distance correction factor is added to the repulsive potential field function to solve the GNRON problem. The regular hexagon-guided method is proposed to improve the local minima problem. Meanwhile, the relative velocity method about the moving objects detection and avoidance is proposed for the dynamic environment. This method considers not only the spatial location but also the magnitude and direction of the velocity of the moving objects, which can avoid dynamic obstacles in time. So the proposed path planning method is suitable for both static and dynamic environments. The virtual environment has been built, and the emulation has been in progress in MATLAB. Simulation results show that the proposed method has promising feasibility and efficiency in the AUV real-time path planning. We demonstrate the performance of the proposed method in the real environment. Experimental results show that the proposed method is capable of avoiding the obstacles efficiently and finding an optimized path.

Evolutionary Computation for Solving Path Planning of an Autonomous Surface Vehicle Using Eulerian Graphs

2018 ◽  
Author(s):  
Mario Arzamendia ◽  
Daniel Gutierrez Reina ◽  
Sergio Toral Marin ◽  
Derlis Gregor ◽  
Hisssam Tawfik
Keyword(s):  
Path Planning ◽  
Evolutionary Computation ◽  
Autonomous Surface Vehicle ◽  
Eulerian Graphs
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