Kinect Sensor-Based Trajectory Planning Method of Collision Avoidance for Industrial Manipulator with an Dexterous Hand

Author(s):  
Xingchen Chen ◽  
Nanfeng Xiao ◽  
Ya Chao
2013 ◽  
Vol 21 (1) ◽  
pp. 20-27
Author(s):  
Rafał Szłapczyński

ABSTRACT In the previous paper the author presented the evolutionary ship trajectory planning method designed to support Traffic Separation Schemes (TSS). This time the extensions of this method are described which allow to combine evolutionary trajectory planning with speed reduction manoeuvres. On TSS regions with higher than usual density of traffic and smaller distances between ships, the course alterations alone are not always sufficient or effective means of collision avoidance. Therefore they must be supplemented by speed reduction manoeuvres to a larger extent than on open waters. The paper includes a brief description of the optimisation problem, descriptions of the new elements of the method (fitness function, algorithms and the evolutionary cycle) and the examples of how the extended method successfully solves the problems unsolvable without applying speed reduction.


2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Shipu Diao ◽  
Xindu Chen ◽  
Lei Wu ◽  
Mingjiang Yang ◽  
Junhui Liu

The intelligent manufacturing system (IMS) is widely used in the surface machining of the workpiece. In the process of ceramic surface grinding, the intelligent machine (manipulator) in IMS is required to automatically plan the collision avoidance trajectory in a complex environment. This paper presents an optimal trajectory planning method of the use of redundant manipulators in the surface grinding of ceramic billet, which is based on trajectory evaluation. The collision avoidance trajectory can be optimized, taking into account several parameters in the trajectory, including the length of the collision avoidance path, the weighted sum of the strokes of all joints, and the duration of the collision avoidance trajectory. Firstly, get the planning task. Secondly, set the planning parameters and obtain a number of collision avoidance trajectories. Finally, the evaluation function is used to evaluate the collision avoidance trajectories and get the optimal collision avoidance trajectory. The performance of the proposed optimal collision avoidance trajectory planning method is validated in different evaluation functions.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shan Fang ◽  
Lan Yang ◽  
Tianqi Wang ◽  
Shoucai Jing

Traffic lights force vehicles to stop frequently at signalized intersections, which leads to excessive fuel consumption, higher emissions, and travel delays. To address these issues, this study develops a trajectory planning method for mixed vehicles at signalized intersections. First, we use the intelligent driver car-following model to analyze the string stability of traffic flow upstream of the intersection. Second, we propose a mixed-vehicle trajectory planning method based on a trigonometric model that considers prefixed traffic signals. The proposed method employs the proportional-integral-derivative (PID) model controller to simulate the trajectory when connected vehicles (equipped with internet access) follow the optimal advisory speed. Essentially, only connected vehicle trajectories need to be controlled because normal vehicles simply follow the connected vehicles according to the Intelligent Driver Model (IDM). The IDM model aims to minimize traffic oscillation and ensure that all vehicles pass the signalized intersection without stopping. The results of a MATLAB simulation indicate that the proposed method can reduce fuel consumption and NOx, HC, CO2, and CO concentrations by 17%, 22.8%, 17.8%, 17%, and 16.9% respectively when the connected vehicle market penetration is 50 percent.


2021 ◽  
Author(s):  
Heqiang Tian ◽  
Jingbo Pan ◽  
Yu Gao ◽  
Bin Tian ◽  
Debao Meng ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document