![]() ![]() Luo Haitao Liu Yuwang Chen Zhengcang Leng Yuquan Yang, Yang Song, Yuntao Pan, Hongtao Cheng, Yong Feng, Hansheng Wu, HuapengĬo- Simulation Control of Robot Arm Dynamics in ADAMS and MATLAB International Nuclear Information System (INIS) Furthermore, the functionality of the simulation software presented in this paper is proved to be suitable for the development of the robotic and computer vision application. As a result, the proposed visual control scheme can successfully drive the EAMA robot to approach and track the target tile until the robot reaches the desired position. ![]() In the experiments, the proposed method was implemented in a simulation environment to position and track a target graphite tile with the EAMA robot. This article presents an autonomous robot control to cope with the robot positioning problem, which is a visual servo approach in context of tile grasping for the EAMA robot. Due to the 9-m-long cantilever arm, the large flexibility of the EAMA robot introduces a problem in the accurate positioning. Yang, Yang, E-mail: [Institute of Plasma Physics, Chinese Academy of Sciences, 350 Shushanhu Rd, Hefei, Anhui (China) Song, Yuntao Pan, Hongtao Cheng, Yong Feng, Hansheng [Institute of Plasma Physics, Chinese Academy of Sciences, 350 Shushanhu Rd, Hefei, Anhui (China) Wu, Huapeng [Lappeenranta University of Technology, Skinnarilankatu 34, Lappeenranta (Finland)įor the inspection and light-duty maintenance of the vacuum vessel in the EAST tokamak, a serial robot arm, called EAST articulated maintenance arm, is developed. It is observed that the RDPSO algorithm converges to the optimal solution faster and more accurately than the other approaches without significantly increasing the computational demand, memory and communication complexity.Visual servo simulation of EAST articulated maintenance arm robotĮnergy Technology Data Exchange (ETDEWEB) Moreover, the RDPSO is further compared with the best performing algorithms within a population of 14 e-pucks. ![]() The simulated experimental results show the superiority of the previously presented Robotic Darwinian Particle Swarm Optimization (RDPSO), evidencing that sociobiological inspiration is useful to meet the challenges of robotic applications that can be described as optimization problems (e.g., search and rescue). This paper presents experiments conducted to benchmark five state-of-the-art algorithms for cooperative exploration tasks. Moreover, such techniques tend to fail in finding targets within dynamic and unstructured environments. For instance, exhaustive multi-robot search techniques, such as sweeping the environment, allow for a better avoidance of local solutions but require too much time to find the optimal one. This is motivated by the gradual growth of swarm robotics solutions in situations where conventional search cannot find a satisfactory solution. Subsequently, the most attractive techniques are evaluated and compared by highlighting their most relevant features. a b s t r a c t This paper presents a survey on multi-robot search inspired by swarm intelligence by further classifying and discussing the theoretical advantages and disadvantages of the existing studies. ![]() The Robotic Darwinian Particle Swarm Optimization (RDPSO) algorithm depicts an improved convergence.The three best performing algorithms are deeply compared using 14 e-pucks on a source localization problem.Simulated experiments of a mapping task are carried out to compare the five algorithms.Five state-of-the-art swarm robotic algorithms are described and compared.A survey on multi-robot search inspired on swarm intelligence is presented. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |