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Path Planning for Robotic Arms Based on an Improved RRT Algorithm
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作者 Wei Liu Zhennan Huang +1 位作者 Yingpeng Qu Long Chen 《Open Journal of Applied Sciences》 2024年第5期1214-1236,共23页
The burgeoning robotics industry has catalyzed significant strides in the development and deployment of industrial and service robotic arms, positioning path planning as a pivotal facet for augmenting their operationa... The burgeoning robotics industry has catalyzed significant strides in the development and deployment of industrial and service robotic arms, positioning path planning as a pivotal facet for augmenting their operational safety and efficiency. Existing path planning algorithms, while capable of delineating feasible trajectories, often fall short of achieving optimality, particularly concerning path length, search duration, and success likelihood. This study introduces an enhanced Rapidly-Exploring Random Tree (RRT) algorithm, meticulously designed to rectify the issues of node redundancy and the compromised path quality endemic to conventional RRT approaches. Through the integration of an adaptive pruning mechanism and a dynamic elliptical search strategy within the Informed RRT* framework, our algorithm efficiently refines the search tree by discarding branches that surpass the cost of the optimal path, thereby refining the search space and significantly boosting efficiency. Extensive comparative analysis across both two-dimensional and three-dimensional simulation settings underscores the algorithm’s proficiency in markedly improving path precision and search velocity, signifying a breakthrough in the domain of robotic arm path planning. 展开更多
关键词 robotic Arm Path Planning RRT algorithm Adaptive Pruning Optimization
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Harnessing the Power of Artificial Intelligence in Neuromuscular Disease Rehabilitation: A Comprehensive Review and Algorithmic Approach
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作者 Rocco de Filippis Abdullah Al Foysal 《Advances in Bioscience and Biotechnology》 CAS 2024年第5期289-309,共21页
Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligen... Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence. 展开更多
关键词 Neuromuscular Diseases REHABILITATION Artificial Intelligence Machine Learning robotic-Assisted Therapy Virtual Reality Personalized Treatment Motor Function Assistive Technologies algorithmic Rehabilitation
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CALIBRATION OF A 6-DOF SPACE ROBOT USING GENETIC ALGORITHM 被引量:16
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作者 LIU Yu JIANG Yanshu +1 位作者 LIANG Bin XU Wenfu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2008年第6期6-13,共8页
The kinematic error model of a 6-DOF space robot is deduced, and the cost function of kinematic parameter identification is built. With the aid of the genetic algorithm (GA) that has the powerful global adaptive pro... The kinematic error model of a 6-DOF space robot is deduced, and the cost function of kinematic parameter identification is built. With the aid of the genetic algorithm (GA) that has the powerful global adaptive probabilistic search ability, 24 parameters of the robot are identified through simulation, which makes the pose (position and orientation) accuracy of the robot a great improvement. In the process of the calibration, stochastic measurement noises are considered. Lastly, generalization of the identified kinematic parameters in the whole workspace of the robot is discussed. The simulation results show that calibrating the robot with GA is very stable and not sensitive to measurement noise. Moreover, even if the robot's kinematic parameters are relative, GA still has strong search ability to find the optimum solution. 展开更多
关键词 robot calibration Position and orientation accuracy Measurement noises Genetic algorithm
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A Configuration Deactivation Algorithm for Boosting Probabilistic Roadmap Planning of Robots 被引量:4
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作者 Mika T. Rantanen Martti Juhola 《International Journal of Automation and computing》 EI 2012年第2期155-164,共10页
We present a method to improve the execution time used to build the roadmap in probabilistic roadmap planners. Our method intelligently deactivates some of the configurations during the learning phase and allows the p... We present a method to improve the execution time used to build the roadmap in probabilistic roadmap planners. Our method intelligently deactivates some of the configurations during the learning phase and allows the planner to concentrate on those configurations that axe most likely going to be useful when building the roadmap. The method can be used with many of the existing sampling algorithms. We ran tests with four simulated robot problems typical in robotics literature. The sampling methods applied were purely random, using Halton numbers, Gaussian distribution, and bridge test technique. In our tests, the deactivation method clearly improved the execution times. Compared with pure random selections, the deactivation method also significantly decreased the size of the roadmap, which is a useful property to simplify roadmap planning tasks. 展开更多
关键词 Probabilistic roadmaps motion planning collision avoidance sampling algorithms robotics.
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Robot path planning using genetic algorithms 被引量:1
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作者 朴松昊 洪炳熔 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2001年第3期215-217,共3页
Presents a strategy for soccer robot path planning using genetic algorithms for which, real number coding method is used, to overcome the defects of binary coding method, and the double crossover operation adopted, to... Presents a strategy for soccer robot path planning using genetic algorithms for which, real number coding method is used, to overcome the defects of binary coding method, and the double crossover operation adopted, to avoid the common defect of early convergence and converge faster than the standard genetic algorithms concludes from simulation results that the method is effective for robot path planning. 展开更多
关键词 path planning soccer robot genetic algorithms
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NOVEL APPROACH FOR ROBOT PATH PLANNING BASED ON NUMERICAL ARTIFICIAL POTENTIAL FIELD AND GENETIC ALGORITHM 被引量:2
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作者 WANG Weizhong ZHAO Jie GAO Yongsheng CAI Hegao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2006年第3期340-343,共4页
A novel approach for collision-free path planning of a multiple degree-of-freedom (DOF) articulated robot in a complex environment is proposed. Firstly, based on visual neighbor point (VNP), a numerical artificial... A novel approach for collision-free path planning of a multiple degree-of-freedom (DOF) articulated robot in a complex environment is proposed. Firstly, based on visual neighbor point (VNP), a numerical artificial potential field is constructed in Cartesian space, which provides the heuristic information, effective distance to the goal and the motion direction for the motion of the robot joints. Secondly, a genetic algorithm, combined with the heuristic rules, is used in joint space to determine a series of contiguous configurations piecewise from initial configuration until the goal configuration is attained. A simulation shows that the method can not only handle issues on path planning of the articulated robots in environment with complex obstacles, but also improve the efficiency and quality of path planning. 展开更多
关键词 robot Path planning Artificial potential field Genetic algorithm
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Design of Robotic Visual Servo Control Based on Neural Network and Genetic Algorithm 被引量:9
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作者 Hong-Bin Wang Mian Liu 《International Journal of Automation and computing》 EI 2012年第1期24-29,共6页
A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation (BP) neural network is used to make a direct transition from image feature to joint angles without req... A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation (BP) neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control. 展开更多
关键词 Visual servo image Jacobian back propagation (BP) neural network genetic algorithm robot control
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Optimization of Path Planning for Construction Robots Based on Multiple Advanced Algorithms 被引量:1
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作者 Kang Tan 《Journal of Computer and Communications》 2018年第7期1-13,共13页
There are many processes involved in construction, it is necessary to optimize the path planning of construction robots. Most researches focused more on optimization algorithms, but less on comparative analysis based ... There are many processes involved in construction, it is necessary to optimize the path planning of construction robots. Most researches focused more on optimization algorithms, but less on comparative analysis based on the advantages and shortcomings of these algorithms. Therefore, the innovation of this paper is to analyze three advanced optimization algorithms (genetic algorithm, hybrid particle swarm algorithm and ant colony algorithm) and discuss how these algorithms can improve the optimization performance by adjusting parameters. Finally, the three algorithms are compared and analyzed to find an optimization algorithm that is suitable for path planning optimization of construction robots. The purpose of the optimization is to obtain the maximum benefit with the least cost and complete project in an efficient and economical way. 展开更多
关键词 PATH PLANNING Construction robotS OPTIMIZATION algorithm
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Multi-objective Optimization of a Parallel Ankle Rehabilitation Robot Using Modified Differential Evolution Algorithm 被引量:13
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作者 WANG Congzhe FANG Yuefa GUO Sheng 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2015年第4期702-715,共14页
Dimensional synthesis is one of the most difficult issues in the field of parallel robots with actuation redundancy. To deal with the optimal design of a redundantly actuated parallel robot used for ankle rehabilitati... Dimensional synthesis is one of the most difficult issues in the field of parallel robots with actuation redundancy. To deal with the optimal design of a redundantly actuated parallel robot used for ankle rehabilitation, a methodology of dimensional synthesis based on multi-objective optimization is presented. First, the dimensional synthesis of the redundant parallel robot is formulated as a nonlinear constrained multi-objective optimization problem. Then four objective functions, separately reflecting occupied space, input/output transmission and torque performances, and multi-criteria constraints, such as dimension, interference and kinematics, are defined. In consideration of the passive exercise of plantar/dorsiflexion requiring large output moment, a torque index is proposed. To cope with the actuation redundancy of the parallel robot, a new output transmission index is defined as well. The multi-objective optimization problem is solved by using a modified Differential Evolution(DE) algorithm, which is characterized by new selection and mutation strategies. Meanwhile, a special penalty method is presented to tackle the multi-criteria constraints. Finally, numerical experiments for different optimization algorithms are implemented. The computation results show that the proposed indices of output transmission and torque, and constraint handling are effective for the redundant parallel robot; the modified DE algorithm is superior to the other tested algorithms, in terms of the ability of global search and the number of non-dominated solutions. The proposed methodology of multi-objective optimization can be also applied to the dimensional synthesis of other redundantly actuated parallel robots only with rotational movements. 展开更多
关键词 ankle rehabilitation parallel robot multi-objective optimization differential evolution algorithm
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Path Planning of Continuum Robot Based on a New Improved Particle Swarm Optimization Algorithm 被引量:5
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作者 Fang Gao Qiang Zhao Gui-Xian Li 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2013年第4期78-84,共7页
Continuum robot is a new type of biomimetic robot,which realizes the motion by bending some parts of its body.So its path planning becomes more difficult even compared with hyper-redundant robots.In this paper a circu... Continuum robot is a new type of biomimetic robot,which realizes the motion by bending some parts of its body.So its path planning becomes more difficult even compared with hyper-redundant robots.In this paper a circular arc spline interpolating method is proposed for the robot shape description,and a new two-stage position-selectable-updating particle swarm optimization(TPPSO)algorithm is put forward to solve this path planning problem.The algorithm decomposes the standard PSO velocity’s single-step updating formula into twostage multi-point updating,specifically adopting three points as candidates and selecting the best one as the updated position in the first half stage,and similarly taking seven points as candidates and selecting the best one as the final position in the last half stage.This scheme refines and widens each particle’s searching trajectory,increases the updating speed of the individual best,and improves the converging speed and precision.Aiming at the optimization objective to minimize the sum of all the motion displacements of every segmental points and all the axial stretching or contracting displacements of every segment,the TPPSO algorithm is used to solve the path planning problem.The detailed solution procedure is presented.Numerical examples of five path planning cases show that the proposed algorithm is simple,robust,and efficient. 展开更多
关键词 continuum robot path planning particle swarm optimization algorithm
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Path planning based on sliding window and variant A* algorithm for quadruped robot 被引量:2
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作者 张慧 Rong Xuewen +3 位作者 Li Yibin Li Bin Zhang Junwen Zhang Qin 《High Technology Letters》 EI CAS 2016年第3期334-342,共9页
In order to improve the adaptability of the quadruped robot in complex environments,a path planning method based on sliding window and variant A* algorithm for quadruped robot is presented. To improve the path plannin... In order to improve the adaptability of the quadruped robot in complex environments,a path planning method based on sliding window and variant A* algorithm for quadruped robot is presented. To improve the path planning efficiency and robot security,an incremental A* search algorithm( IA*) and the A* algorithm having obstacle grids extending( EA*) are proposed respectively. The IA* algorithm firstly searches an optimal path based on A* algorithm,then a new route from the current path to the new goal projection is added to generate a suboptimum route incrementally. In comparison with traditional method solving path planning problem from scratch,the IA* enables the robot to plan path more efficiently. EA* extends the obstacle by means of increasing grid g-value,which makes the route far away from the obstacle and avoids blocking the narrow passage. To navigate the robot running smoothly,a quadratic B-spline interpolation is applied to smooth the path.Simulation results illustrate that the IA* algorithm can increase the re-planning efficiency more than 5 times and demonstrate the effectiveness of the EA* algorithm. 展开更多
关键词 QUADRUPED robot path planning SLIDING WINDOW A* algorithm
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Ant Colony System Algorithm for Real-Time Globally Optimal Path Planning of Mobile Robots 被引量:26
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作者 TAN Guan-Zheng HE Huan SLOMAN Aaron 《自动化学报》 EI CSCD 北大核心 2007年第3期279-285,共7页
为活动机器人计划的即时全球性最佳的路径的一个新奇方法基于蚂蚁殖民地系统(交流) 被建议算法。这个方法包括三步:第一步正在利用 MAKLINK 图理论建立活动机器人的空间模型,第二步正在利用 Dijkstra 算法发现一条非最优的没有碰撞的... 为活动机器人计划的即时全球性最佳的路径的一个新奇方法基于蚂蚁殖民地系统(交流) 被建议算法。这个方法包括三步:第一步正在利用 MAKLINK 图理论建立活动机器人的空间模型,第二步正在利用 Dijkstra 算法发现一条非最优的没有碰撞的路径,并且第三步正在利用 ACS 算法优化非最优的路径的地点以便产生全球性最佳的路径。建议方法是有效的并且能在即时路径被使用活动机器人计划的计算机模拟实验表演的结果。建议方法比与优秀人材模型一起基于基因算法计划方法的路径处于集中速度,答案变化,动态集中行为,和计算效率有更好的性能,这被验证了。 展开更多
关键词 蚁群系统 运算法则 自动化系统 计算机技术
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Genetic Algorithm Based Combinatorial Auction Method for Multi-Robot Task Allocation 被引量:1
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作者 龚建伟 黄宛宁 +1 位作者 熊光明 满益明 《Journal of Beijing Institute of Technology》 EI CAS 2007年第2期151-156,共6页
An improved genetic algorithm is proposed to solve the problem of bad real-time performance or inability to get a global optimal/better solution when applying single-item auction (SIA) method or combinatorial auctio... An improved genetic algorithm is proposed to solve the problem of bad real-time performance or inability to get a global optimal/better solution when applying single-item auction (SIA) method or combinatorial auction method to multi-robot task allocation. The genetic algorithm based combinatorial auction (GACA) method which combines the basic-genetic algorithm with a new concept of ringed chromosome is used to solve the winner determination problem (WDP) of combinatorial auction. The simulation experiments are conducted in OpenSim, a multi-robot simulator. The results show that GACA can get a satisfying solution in a reasonable shot time, and compared with SIA or parthenogenesis algorithm combinatorial auction (PGACA) method, it is the simplest and has higher search efficiency, also, GACA can get a global better/optimal solution and satisfy the high real-time requirement of multi-robot task allocation. 展开更多
关键词 MULTI-robot task allocation combinatorial auctions genetic algorithm
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Design of Fuzzy Controller for Robot Manipulators Using Bacterial Foraging Optimization Algorithm 被引量:3
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作者 Mickael Aghajarian Kourosh Kiani Mohammad Mehdi Fateh 《Journal of Intelligent Learning Systems and Applications》 2012年第1期53-58,共6页
Trial and error method can be used to find a suitable design of a fuzzy controller. However, there are many options including fuzzy rules, Membership Functions (MFs) and scaling factors to achieve a desired performanc... Trial and error method can be used to find a suitable design of a fuzzy controller. However, there are many options including fuzzy rules, Membership Functions (MFs) and scaling factors to achieve a desired performance. An optimiza-tion algorithm facilitates this process and finds an optimal design to provide a desired performance. This paper presents a novel application of the Bacterial Foraging Optimization algorithm (BFO) to design a fuzzy controller for tracking control of a robot manipulator driven by permanent magnet DC motors. We use efficiently the BFO algorithm to form the rule base and MFs. The BFO algorithm is compared with a Particle Swarm Optimization algorithm (PSO). Performance of the controller in the joint space and in the Cartesian space is evaluated. Simulation results show superiority of the BFO algorithm to the PSO algorithm. 展开更多
关键词 BFO algorithm PSO algorithm Fuzzy CONTROL robot MANIPULATOR Tracking CONTROL
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Optimizing Deep Learning Parameters Using Genetic Algorithm for Object Recognition and Robot Grasping 被引量:2
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作者 Delowar Hossain Genci Capi Mitsuru Jindai 《Journal of Electronic Science and Technology》 CAS CSCD 2018年第1期11-15,共5页
The performance of deep learning(DL)networks has been increased by elaborating the network structures. However, the DL netowrks have many parameters, which have a lot of influence on the performance of the network. We... The performance of deep learning(DL)networks has been increased by elaborating the network structures. However, the DL netowrks have many parameters, which have a lot of influence on the performance of the network. We propose a genetic algorithm(GA) based deep belief neural network(DBNN) method for robot object recognition and grasping purpose. This method optimizes the parameters of the DBNN method, such as the number of hidden units, the number of epochs, and the learning rates, which would reduce the error rate and the network training time of object recognition. After recognizing objects, the robot performs the pick-andplace operations. We build a database of six objects for experimental purpose. Experimental results demonstrate that our method outperforms on the optimized robot object recognition and grasping tasks. 展开更多
关键词 Deep learning(DL) deep belief neural network(DBNN) genetic algorithm(GA) object recognition robot grasping
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Robot stereo vision calibration method with genetic algorithm and particle swarm optimization 被引量:1
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作者 汪首坤 李德龙 +1 位作者 郭俊杰 王军政 《Journal of Beijing Institute of Technology》 EI CAS 2013年第2期213-221,共9页
Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm (GA) and particle swarm optimization (PSO), a ... Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm (GA) and particle swarm optimization (PSO), a three-stage calibration method based on hybrid intelligent optimization is pro- posed for nonlinear camera models in this paper. The motivation is to improve the accuracy of the calibration process. In this approach, the stereo vision calibration is considered as an optimization problem that can be solved by the GA and PSO. The initial linear values can be obtained in the frost stage. Then in the second stage, two cameras' parameters are optimized separately. Finally, the in- tegrated optimized calibration of two models is obtained in the third stage. Direct linear transforma- tion (DLT), GA and PSO are individually used in three stages. It is shown that the results of every stage can correctly find near-optimal solution and it can be used to initialize the next stage. Simula- tion analysis and actual experimental results indicate that this calibration method works more accu- rate and robust in noisy environment compared with traditional calibration methods. The proposed method can fulfill the requirements of robot sophisticated visual operation. 展开更多
关键词 robot stereo vision camera calibration genetic algorithm (GA) particle swarm opti-mization (PSO) hybrid intelligent optimization
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跟踪算法下的果树修剪机器人路径规划设计 被引量:1
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作者 方小菊 黄亦其 《农机化研究》 北大核心 2024年第1期155-158,共4页
以果树修剪机器人为研究对象,基于轨迹跟踪算法对修剪机器人进行作业路径规划,并分别与传统的往复式路径规划算法和跟踪算法进行仿真对比实验分析。分析结果表明:与传统往复式路径规划算法相比,修剪机器人作业过程中漏剪率降低3%,重复... 以果树修剪机器人为研究对象,基于轨迹跟踪算法对修剪机器人进行作业路径规划,并分别与传统的往复式路径规划算法和跟踪算法进行仿真对比实验分析。分析结果表明:与传统往复式路径规划算法相比,修剪机器人作业过程中漏剪率降低3%,重复率降低2.5%;与传统跟踪式路径规划算法相比,修剪机器人作业过程转角范围增大36°,横向轨迹误差降低600mm。 展开更多
关键词 修剪机器人 跟踪算法 路径规划
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基于POE模型的工业机器人运动学参数二次辨识方法研究 被引量:1
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作者 乔贵方 杜宝安 +3 位作者 张颖 田荣佳 刘娣 刘汉忠 《农业机械学报》 EI CAS CSCD 北大核心 2024年第1期419-425,共7页
针对工业机器人在高度制造领域精度不高的问题,本文提出了一种基于POE模型的工业机器人运动学参数二次辨识方法。阐述了基于指数积(Product of exponential, POE)模型的运动学误差模型构建方法,并建立基于POE误差模型的适应度函数;为实... 针对工业机器人在高度制造领域精度不高的问题,本文提出了一种基于POE模型的工业机器人运动学参数二次辨识方法。阐述了基于指数积(Product of exponential, POE)模型的运动学误差模型构建方法,并建立基于POE误差模型的适应度函数;为实现高精度的参数辨识,提出了一种二次辨识方法,先利用改进灰狼优化算法(Improved grey wolf optimizer, IGWO)实现运动学参数误差的粗辨识,初步将Staubli TX60型机器人的平均位置误差和平均姿态误差分别从(0.648 mm, 0.212°)降低为(0.457 mm, 0.166°);为进一步提高机器人的精度性能,再通过LM(Levenberg-Marquard)算法进行参数误差的精辨识,最终将Staubli TX60型机器人平均位置误差和平均姿态误差进一步降低为(0.237 mm, 0.063°),机器人平均位置误差和平均姿态误差分别降低63.4%和70.2%。为了验证上述二次辨识方法的稳定性,随机选取5组辨识数据集和验证数据集进行POE误差模型的参数误差辨识,结果表明提出的二次辨识方法能够稳定、精确地辨识工业机器人运动学参数误差。 展开更多
关键词 串联型工业机器人 改进灰狼优化算法 指数积 参数辨识
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A novel compound biped locomotion algorithm for humanoid robots to realize biped walking
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作者 Ruiwu XIN Nanfeng XIAO 《控制理论与应用(英文版)》 EI 2009年第1期23-28,共6页
In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for th... In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for the humanoid. In the second part, the compound biped locomotion algorithm is presented based on the reference motion and reference Zero Moment Point (ZMP). This novel algorithm includes calculation of the upper body motion and trajectory of the Center of Gravity (COG) of the robot. First, disturbances from the environment are eliminated by the compensational movement of the upper body; then based on the error between a reference ZMP and the real ZMP as well as the relation between ZMP and CoG, the CoG error is calculated, thus leading to the CoG trajectory. Then, the motion of the robot converges to its reference motion, generating stable biped walking. Because the calculation of upper body motion and trajectory of CoG both depend on the reference motion, they can work in parallel, thus providing double insurances against the robot's collapse. Finally, the algorithm is validated by different kinds of simulation experiments. 展开更多
关键词 Humanoid robot Structural design Compound biped locomotion algorithm Simulation experiments
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电力巡检机器人路径规划方法综述 被引量:2
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作者 李刚 智宏鑫 《电力科学与工程》 2024年第4期1-11,共11页
随着电力系统规模和复杂性的不断增加,传统的人工巡检方式已很难满足当下电力巡检要求。巡检机器人因具有安全性、可靠性和智能性已被逐步应用到电力巡检中。机器人在运行过程中通过提前预测、自主决策或智能导航的方式完成全局遍历与... 随着电力系统规模和复杂性的不断增加,传统的人工巡检方式已很难满足当下电力巡检要求。巡检机器人因具有安全性、可靠性和智能性已被逐步应用到电力巡检中。机器人在运行过程中通过提前预测、自主决策或智能导航的方式完成全局遍历与避障。电力巡检的核心任务是规划出一条安全且最优的运行轨迹。系统地分析和梳理了巡检机器人巡检过程中的各类方法;阐述了在变电站和输电线路等不同场景中算法的应用;综述了各类路径规划算法的研究现状和改进方法。在此基础上,对未来电力巡检机器人路径规划的研究和发展方向做出了展望。 展开更多
关键词 电力巡检 巡检机器人 路径规划 智能算法 深度强化学习
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