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Path planning of hyper‐redundant manipulators for narrow spaces

IET Cyber-Systems and Robotics 2022年第3期4卷 251-263页

作者： Haoxiang Su Manlu Liu Hongwei Liu Jianwen Huo Songlin Gou Qing Su School of Information Engineering Southwest University of Science and TechnologyMian YangChina Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Mian YangChina School of Manufacturing Science and Engineering Southwest University of Science and TechnologyMian YangChina

Compared with the traditional manipulator,the hyper‐redundant manipulator has the advantage of high flexibility,which is particularly suitable for all kinds of complex working ***,the complex space environment requires the hyper‐redundant manipulator to have stronger obstacle avoidance ability and *** order to solve the problems of a large amount of calculation and poor obstacle avoidance effects in the path planning of the hyper‐redundant manipulator,this paper introduces the‘backbone curve’approach,which transforms the problem of solving joint path points into the behaviour of determining the backbone *** the backbone curve approach is used to design the curve that meets the requirements of obstacle avoidance and the end pose,the least squares fitting and the improved space joint fitting are used to match the plane curve and the space curve respectively,and the angle value of each joint of the manipulator is limited by the ***,a fusion obstacle avoidance algorithm is proposed to obtain the joint path points of the hyper‐redundant *** with the classic Jacobian iteration method,this method can avoid obstacles better,has the advantages of simple calculation,high efficiency,and can fully reflect the geometric characteristics of the *** experiments have proven the feasibility of the algorithm.

关键词： convergence dexterous manipulators geometric algebra motion planning

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Scene images and text information‐based object location of robot grasping

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IET Cyber-Systems and Robotics 2022年第2期4卷 116-130页

作者： Zhichao Liu Kaixuan Ding Qingyang Xu Yong Song Xianfeng Yuan Yibin Li School of Mechanical Electrical&Information EngineeringShandong UniversityWeihaiChina School of Control Science and Engineering Shandong UniversityJinanChina

With the rapid development of artificial intelligence(AI),the application of this technology in the medical field is becoming increasingly extensive,along with a gradual increase in the amount of intelligent equipment in *** robots can save human resources and replace nursing staff to achieve some *** view of the phenomenon of mobile service robots'grabbing and distribution of patients'drugs in hospitals,a real‐time object detection and positioning system based on image and text information is proposed,which realizes the precise positioning and tracking of the grabbing objects and completes the grasping of a specific object(medicine bottle).The lightweight object detection model NanoDet is used to learn the features of the grasping objects and the object category,and bounding boxes are ***,the images in the bounding boxes are enhanced to overcome unfavourable factors,such as a small object *** text detection and recognition model PP‐OCR is used to detect and recognise the enhanced images and extract the text *** object information provided by the two models is fused,and the text recognition result is matched with the object detection box to achieve the precise posi-tioning of the grasping *** kernel correlation filter(KCF)tracking algorithm is introduced to achieve real‐time tracking of specific objects to precisely control the robot's *** deep learning models adopt lightweight networks to facilitate direct *** experiments show that the proposed robot grasping detection system has high reliability,accuracy and real‐time performance.

关键词： dexterous manipulators neural network‐based,robot control robot vision service robots

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