Path planning and design for AFM based nano-manipulation using probability distribution

Author(s):  
Shuai Yuan ◽  
Lianqing Liu ◽  
Zhidong Wang ◽  
Jingyi Xing ◽  
Ning Xi ◽  
...  
Robotica ◽  
2008 ◽  
Vol 26 (2) ◽  
pp. 229-239 ◽  
Author(s):  
G. Carbone ◽  
M. Ceccarelli ◽  
P. J. Oliveira ◽  
S. F. P. Saramago ◽  
J. C. M. Carvalho

SUMMARYIn this paper, a novel algorithm is formulated and implemented for optimum path planning of parallel manipulators. A multi-objective optimisation problem has been formulated for an efficient numerical solution procedure through kinematic and dynamic features of manipulator operation. Computational economy has been obtained by properly using a genetic algorithm to search an optimal solution for path spline-functions. Numerical characteristics of the numerical solving procedure have been outlined through a numerical example applied to Cassino Parallel Manipulator (CaPaMan) both for path planning and design purposes.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Fengtao Xiang ◽  
Keqin Chen ◽  
Jiongming Su ◽  
Hongfu Liu ◽  
Wanpeng Zhang

Unmanned aerial vehicles (UAVs) are gradually used in logistics transportation. They are forbidden to fly in some airspace. To ensure the safety of UAVs, reasonable path planning and design is one of the key factors. Aiming at the problem of how to improve the success rate of unmanned aerial vehicle (UAV) maneuver penetration, a method of UAV penetration path planning and design is proposed. Ant colony algorithm has strong path planning ability in biological swarm intelligence algorithm. Based on the modeling of UAV planning and threat factors, improved ant colony algorithm is used for UAV penetration path planning and design. It is proposed that the path with the best pheromone content is used as the planning path. Some principles are given for using ant colony algorithm in UAV penetration path planning. By introducing heuristic information into the improved ant colony algorithm, the convergence is completed faster under the same number of iteratives. Compared with classical methods, the total steps reduced by 56% with 50 ant numbers and 200 iterations. 62% fewer steps to complete the first iteration. It is found that the optimal trajectory planned by the improved ant colony algorithm is smoother and the shortest path satisfying the constraints.


2018 ◽  
pp. 172-182 ◽  
Author(s):  
Shengmin CAO

This paper mainly studies the application of intelligent lighting control system in different sports events in large sports competition venues. We take the Xiantao Stadium, a large­scale sports competition venue in Zaozhuang City, Shandong Province as an example, to study its intelligent lighting control system. In this paper, the PID (proportion – integral – derivative) incremental control model and the Karatsuba multiplication model are used, and the intelligent lighting control system is designed and implemented by multi­level fuzzy comprehensive evaluation model. Finally, the paper evaluates the actual effect of the intelligent lighting control system. The research shows that the intelligent lighting control system designed in this paper can accurately control the lighting of different sports in large stadiums. The research in this paper has important practical significance for the planning and design of large­scale sports competition venues.


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