Golden Path Search Algorithm for the KSA Scheme

Author(s):  
Ching-Kang Ing ◽  
Chin-Yi Lin ◽  
Po-Hsiang Peng ◽  
Yu-Ming Hsieh ◽  
Fan-Tien Cheng
2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Tie Zhang ◽  
Xiaohong Liang ◽  
Ye Yu ◽  
Bin Zhang

The angular variation of the joints may be large, and collision between workpieces and tools may occur in robotic grinding. Therefore, this paper proposes an optimal robotic grinding path search algorithm based on the recursive method. The algorithm is optimized by changing the position of the tool coordinate system on the belt wheel; thus, the pose of the robot during grinding is adjusted. First, the position adjustment formula of the tool coordinate system is proposed, and a coordinate plane is established to describe the grinding path of the robot based on the position adjustment formula. Second, the ordinate value of this coordinate plane is dispersed to obtain the search field of the optimal robotic grinding path search algorithm. Third, an optimal robotic grinding path search algorithm is proposed based on the recursive method and single-step search process. Finally, the algorithm is implemented on the V-REP platform. Robotic grinding paths for V-shaped workpieces and S-shaped workpieces are generated using this algorithm, and a grinding experiment is performed. The experimental results show that the robotic grinding paths generated by this algorithm can smoothly complete grinding operations and feature a smaller angular variation of the joint than other methods and no collision.


2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Shudao Zhou ◽  
Ao Shen ◽  
Min Wang ◽  
Shuling Peng ◽  
Zhanhua Liu

In order to make multirotor unmanned aerial vehicles (UAV) compose a desired dense formation and improve the practicality of UAV formation, a distributed algorithm based on fuzzy logic was proposed. The airflow created by multirotor UAVs was analyzed according to the structure of the multirotor UAV and the characteristic equation of the fluid. This paper presented a dynamic model for the process of formation of and path search algorithm based on this model. The membership function in this model combines the factors of position, flow field, and movement. Integrating the dynamic model and its desired position in formations, each UAV evaluates the surrounding points and then selects the direction for step motion. Through simulation, this algorithm was improved by a by-step formation approach, and the effectiveness of this method in dense formation of multirotor UAVs was proved.


2011 ◽  
Vol 23 (4) ◽  
pp. 567-581 ◽  
Author(s):  
Evgeni Magid ◽  
◽  
Takashi Tsubouchi ◽  
Eiji Koyanagi ◽  
Tomoaki Yoshida ◽  
...  

Rescue robotics applies search and rescue robots to expand rescue capabilities while increasing safety. Mobile robots working at a disaster site are monitored remotely by operators who may not be able to see the site well and select work paths appropriately. Our goal is to provide a “pilot system” that can propose options for traversing 3D debris environments. This requires a special debris path search algorithm and an appropriately defined search tree ensuring smooth exploration. To make a path search feasible in huge real state space we discretize search space and robot movement before a search. In this paper we present path quality estimation and search tree branching functionF, which defines search tree building process online through node opening and branching. Well-defined functionFremoves unsuitable search directions from the search tree and enables dynamic path planning accounting for debris. Exhaustive simulation was used to structure and analyze data. Experiments confirmed the feasibility of our approach.


2013 ◽  
Author(s):  
Eunju Kim ◽  
◽  
YONGZHE XU ◽  
Kyunjoo Lee ◽  
Jaesug Ki ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
De-Xin Yu ◽  
Zhao-Sheng Yang ◽  
Yao Yu ◽  
Xiu-Rong Jiang

Combined with improved Pallottino parallel algorithm, this paper proposes a large-scale route search method, which considers travelers’ route choice preferences. And urban road network is decomposed into multilayers effectively. Utilizing generalized travel time as road impedance function, the method builds a new multilayer and multitasking road network data storage structure with object-oriented class definition. Then, the proposed path search algorithm is verified by using the real road network of Guangzhou city as an example. By the sensitive experiments, we make a comparative analysis of the proposed path search method with the current advanced optimal path algorithms. The results demonstrate that the proposed method can increase the road network search efficiency by more than 16% under different search proportion requests, node numbers, and computing process numbers, respectively. Therefore, this method is a great breakthrough in the guidance field of urban road network.


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