Novel ARC-Fuzzy Coordinated Automatic Tracking Control of Four-Wheeled Mobile Robot

Four-wheeled,individual-driven,nonholonomic structured mobile robots are widely used in industries for automated work,inspection and explora-tion purposes.The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure.The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots.However,there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis’s motion.As a result,the mobile robot has lim-ited performance,such as chattering during curved movement.In this research work,a three-tiered adaptive robust control with fuzzy parameter estimation,including dynamic modeling,direct torque control and wheel slip control is pro-posed.Fuzzy logic-based parameter estimation is a valuable tool for adjusting adaptive robust controller(ARC)parameters and tracking the trajectories with less tracking error as well as high tracking accuracy.This research considers the O type and 8 type trajectories for performance analysis of the proposed novel control technique.Our suggested approach outperforms the existing control methods such as Fuzzy,proportional–integral–derivative(PID)and adaptive robust controller with discrete projection(ARC–DP).The experimental results show that the scheduled performance index decreases by 2.77%and 4.76%.All the experimen-tal simulations obviously proved that the proposed ARC-Fuzzy performed well in smooth groud surfaces compared to other approaches.

Coordinated control strategy for robotic-assisted gait training with partial body weight support

Walking is the most basic and essential part of the activities of daily living. To enable the elderly and non-ambulatory gait-impaired patients, the repetitive practice of this task, a novel gait training robot(GTR) was designed followed the end-effector principle, and an active partial body weight support(PBWS) system was introduced to facilitate successful gait training. For successful establishment of a walking gait on the GTR with PBWS, the motion laws of the GTR were planned to enable the phase distribution relationships of the cycle step, and the center of gravity(COG) trajectory of the human body during gait training on the GTR was measured. A coordinated control strategy was proposed based on the impedance control principle. A robotic prototype was developed as a platform for evaluating the design concepts and control strategies. Preliminary gait training with a healthy subject was implemented by the robotic-assisted gait training system and the experimental results are encouraging.

Assistive Robotics for Upper Limb Physical Rehabilitation:A Systematic Review and Future Prospects

Physical assistive robotics are oriented to support and improve functional capacities of people.In physical rehabilitation,robots are indeed useful for functional recovery of affected limb.However,there are still open questions related to technological aspects.This work presents a systematic review of upper limb rehabilitation robotics in order to analyze and establish technological challenges and future directions in this area.A bibliometric analysis was performed for the systematic literature review.Literature from the last six years,conducted between August 2020 and May 2021,was reviewed.The methodology for the literature search and a bibliometric analysis of the metadata are presented.After a preliminary search resulted in 820 articles,a total of 66 articles were included.A concurrency network and bibliographic analysis were provided.And an analysis of occurrences,taxonomy,and rehabilitation robotics reported in the literature is presented.This review aims to provide to the scientific community an overview of the state of the art in assistive robotics for upper limb physical rehabilitation.The literature analysis allows access to a gap of unexplored options to define the technological prospects applied to upper limb physical rehabilitation robotics.

IMMUNE GENETIC ALGORITHM FOR THE PATH PLANNING OF TIGHTLY COORDINATED TWO-ROBOT MANIPULATORS

A novel algorithm, the immune genetic algorithm based on multi-agent, isproposed for the path planning of tightly coordinated two-robot manipulators, which constructsmainly immune operators accomplished by three steps: defining strategies and methods of multi-agent,calculating virtual forces acting on an agent, and constructing immune operators and performingimmunization during the evolutionary process. It is illustrated to be able to restrain thedegenerate phenomenon effectively and improve the searching ability with high converging speed.

Coordinated control and autonomous grasp with multifingered robot hands

Presents major achievements in researches on coordinated control with multifingered robot hands by first briefing the present status of researches on multifingered robot hands, then discussing the coordinated control with multifingered robot hands, and finally exploring the way of achieving autonomous grasp, and thoughts on future researches.

Intelligent Sensing and Control of Road Construction Robot Scenes Based on Road Construction

Automatic control technology is the basis of road robot improvement,according to the characteristics of construction equipment and functions,the research will be input type perception from positioning acquisition,real-world monitoring,the process will use RTK-GNSS positional perception technology,by projecting the left side of the earth from Gauss-Krueger projection method,and then carry out the Cartesian conversion based on the characteristics of drawing;steering control system is the core of the electric drive unmanned module,on the basis of the analysis of the composition of the steering system of unmanned engineering vehicles,the steering system key components such as direction,torque sensor,drive motor and other models are established,the joint simulation model of unmanned engineering vehicles is established,the steering controller is designed using the PID method,the simulation results show that the control method can meet the construction path demand for automatic steering.The path planning will first formulate the construction area with preset values and realize the steering angle correction during driving by PID algorithm,and never realize the construction-based path planning,and the results show that the method can control the straight path within the error of 10 cm and the curve error within 20 cm.With the collaboration of various modules,the automatic construction simulation results of this robot show that the design path and control method is effective.

Adaptive neural network control for coordinated motion of a dual-arm space robot system with uncertain parameters

Control of coordinated motion between the base attitude and the arm joints of a free-floating dual-arm space robot with uncertain parameters is discussed. By combining the relation of system linear momentum conversation with the Lagrangian approach, the dynamic equation of a robot is established. Based on the above results, the free-floating dual-arm space robot system is modeled with RBF neural networks, the GL matrix and its product operator. With all uncertain inertial system parameters, an adaptive RBF neural network control scheme is developed for coordinated motion between the base attitude and the arm joints. The proposed scheme does not need linear parameterization of the dynamic equation of the system and any accurate prior-knowledge of the actual inertial parameters. Also it does not need to train the neural network offline so that it would present real-time and online applications. A planar free-floating dual-arm space robot is simulated to show feasibility of the proposed scheme.

FUZZY COORDINATION AND FORCE/POSITION CONTROL OF ROBOTIC MANIPULATOR

It is crucial for implementing force/position control of robotic manipulator under the constraint of unknown environment to determine the force control and the position control directions. This paper presents an on line algorithm to real timely estimate the tangent and the normal vectors of the constraint surface based on the measured contact force under the consideration of frictional force. A fuzzy synthesis policy is proposed to coordinate the conflict between the compliant force control and the stiff position control. An experimental study on an AdeptThree, a SCARA type robotic manipulator, is conducted. The experimental results show that the policy presented in the paper is effective.

Structure design and coordinated motion analysis of bionic crocodile robot

Crocodiles,one of the oldest and most resilient species on Earth,have demonstrated remarkable locomotor abilities both on land and in water,evolving over millennia to adapt to diverse environ-ments.In this study,we draw inspiration from crocodiles and design a highly biomimetic crocodile robot equipped with multiple degrees of freedom and articulated trunk joints.This design is based on comprehensive analysis of the structural and motion characteristics of real crocodiles.The bionic crocodile robot has a problem of limb-torso incoordination during movement.To solve this problem,we used the D-H method for both forward and inverse kinematics analysis of the robot's legs and spine.Through a series of simulation experiments,we investigated the robot's motion stability,fault tolerance,and adaptability to environments in two motor patterns:with and without spine and tail movements.The experimental results show that the bionic crocodile robot exhibits superior motion performance when the spine and tail cooperate with the extremities.This study not only demonstrates the potential of biomimicry in robotics but also underscores the significance of understanding how nature's designs can inform and enhance technological innovations.

Inter-limb and intra-limb coordination control of quadruped robots

To realize the coordinated and stable rhythmic motion of quadruped robots （QRs）, the locomotion control method of QRs based on central pattern generator （CPG） was explored. In tradi- tional control strategies based on CPG, few CPG models care about the intra-limb coordination of QRs, and the durations of stance phase and swing phase are always equal. In view of these deficien- cies, a new and simpler multi-joint coordinated control method for both inter-limb and intra-limb was proposed in this paper. A layered CPG control network to realize the locomotion control of QRs was constructed by using modified Hopf oscillators. The coupled relationships among hip joints of all limbs and between hip joint and knee joint within a limb were established. Using the co-simulation method of ADAMS and MATLAB/Simulink, various gait simulation experiments were carried out and the effectiveness of the designed control network was tested. Simulation results show that the pro- posed control method is effective for QRs and can meet the control requirements of QRs＇ gaits with different duty factors.

Dynamic Coordination of Uncalibrated Hand/Eye Robotic System Based on Neural Network

A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.

Robot Vision System for Coordinate Measurement of Feature Points on Large Scale Automobile Part

In this paper,we present a robot vision based system for coordinate measurement of feature points on large scale automobile parts.Our system consists of an industrial 6-DOF robot mounted with a CCD camera and a PC.The system controls the robot into the area of feature points.The images of measuring feature points are acquired by the camera mounted on the robot.3D positions of the feature points are obtained from a model based pose estimation that applies to the images.The measured positions of all feature points are then transformed to the reference coordinate of feature points whose positions are obtained from the coordinate measuring machine（CMM）.Finally,the point-to-point distances between the measured feature points and the reference feature points are calculated and reported.The results show that the root mean square error（RMSE） of measure values obtained by our system is less than 0.5 mm.Our system is adequate for automobile assembly and can perform faster than conventional methods.

Dual-manipulator Coordinate Motion Planning Scheme for Robot Satellite

A scheme of dual-manipulator coordination motion planning for robot satellite (RS) is proposed.Based on the analysis of RS motion characteristics in micro-gravity environment, two manipulators are divided into main manipulator and assistant manipulator. Then, four kinds of coordination modes for dual-manipulator RS, namely,stablizing function, counterbalancing function, adjusting function and coorperative operation are presented. Motion planning algorithm for dual-manipulator is also presented.Finally, computer simulation results of the four kinds of coordination modes for a RS experimental model capturing target operation in micro-gravity environment are given.Simulation experiments show that the coordination modes and planning algorithm proposed in this paper are effective.

Research on Multi-robot Coordination Searching Ignition Sources Approach

For the purpose of study on forecasting forest fire behavior,a probability approach was presented to search ignition sources by multi-robot coordination. Firstly,the environment map is built based on Bayes rules. Then,the probability searching strategy based on the environment map was designed. Every grid of the searching area was assigned searching expectation value, and robots selected the grid with the highest expectation value as its searching target. The simulation results show the search time reduces greatly,which proves the feasibility and validity of the given algorithm under unknown fire condition.

New coordination scheme for multi-robot systems based on state space models

A new coordination scheme for multi-robot systems is proposed. A state space model of the multi- robot system is defined and constructed in which the system＇s initial and goal states are included along with the task definition and the system＇s internal and external constraints. Task accomplishment is considered a transition of the system state in its state space （SS） under the system＇s constraints. Therefore, if there exists a connectable path within reachable area of the SS from the initial state to the goal state, the task is realizable. The optimal strategy for the task realization under constraints is investigated and reached by searching for the optimal state transition trajectory of the robot system in the SS. Moreover, if there is no connectable path, which means the task cannot be performed Successfully, the task could be transformed to be realizable by making the initial state and the goal state connectable and finding a path connecting them in the system＇s SS. This might be done via adjusting the system＇s configuration and/or task constraints. Experiments of multi-robot formation control with obstacles in the environment are conducted and simulation results show the validity of the proposed method.

Deep-reinforcement-learning-based robot motion strategies for grabbing objects from human hands

Background Robot grasping encompasses a wide range of research areas;however, most studies have been focused on the grasping of only stationary objects in a scene;only a few studies on how to grasp objects from a user's hand have been conducted. In this paper, a robot grasping algorithm based on deep reinforcement learning (RGRL) is proposed. Methods The RGRL takes the relative positions of the robot and the object in a user's hand as input and outputs the best action of the robot in the current state. Thus, the proposed algorithm realizes the functions of autonomous path planning and grasping objects safely from the hands of users. A new method for improving the safety of human-robot cooperation is explored. To solve the problems of a low utilization rate and slow convergence of reinforcement learning algorithms, the RGRL is first trained in a simulation scene, and then, the model para-meters are applied to a real scene. To reduce the difference between the simulated and real scenes, domain randomization is applied to randomly change the positions and angles of objects in the simulated scenes at regular intervals, thereby improving the diversity of the training samples and robustness of the algorithm. Results The RGRL's effectiveness and accuracy are verified by evaluating it on both simulated and real scenes, and the results show that the RGRL can achieve an accuracy of more than 80% in both cases. Conclusions RGRL is a robot grasping algorithm that employs domain randomization and deep reinforcement learning for effective grasping in simulated and real scenes. However, it lacks flexibility in adapting to different grasping poses, prompting future research in achieving safe grasping for diverse user postures.

基于改进YOLO v5的复杂环境下柑橘目标精准检测与定位方法

针对自然环境下柑橘果实机械化采收作业环境复杂和果实状态多样等情况,提出了一种多通道信息融合网络——YOLO v5-citrus,以解决柑橘果实识别精准度低、果实分类模糊和定位精准度低等难题。将不同的柑橘目标通过不同遮挡条件分为“可采摘”和“难采摘”两类,这种分类策略可指导机器人在真实果园中顺序摘取,提高采摘效率并减少机器人本体和末端执行器损坏率。YOLO v5-citrus中,在颈部网络插入多通道信息融合模块,对柑橘的深浅特征信息进行处理,提高柑橘采摘状态识别精度,同时修改颈部网络拼接方法,针对目标柑橘大小进行识别,训练后在识别部分嵌入聚类算法模块,将训练部分识别模糊的柑橘目标进行最后区分。识别后进行深度图像和彩色图像的像素对齐,并通过坐标系转换获取柑橘目标三维坐标。在使用多种增强技术处理的数据集中,YOLO v5-citrus比原始YOLO v5在平均精度均值和精确率上分别提高2.8个百分点与3.7个百分点,表现出更优异的泛化能力。与YOLO v7和YOLO v8等其他主流网络架构相比较,保持了更高的检测精度和更快的检测速度。通过真实果园的检测与定位试验,得到柑橘目标的三维坐标识别定位系统的定位误差为(1.97 mm,0.36 mm,9.63 mm),满足末端执行器的抓取条件。试验结果表明,该模型具有较强的鲁棒性,满足复杂环境下柑橘状态识别要求,可为柑橘园机械采收设备提供技术支持。

虚实坐标智能匹配与自适应三维轨迹规划

针对数字孪生增材修复任务中,物件仿真与真实坐标对应困难、三维轨迹误差较大的问题,提出虚实坐标智能匹配与自适应三维轨迹规划方法。采用图像分割方法获取实际场景下物件的分割图像,通过最小外接矩形预估物件真实坐标,仿真端据此执行旋转与平移操作,调整仿真物件的模型位置,实现坐标智能匹配;为最小化虚实坐标误差,设计基于Attention的多尺度残差UNet图像分割模型,利用多尺度残差模块获取物件多尺度特征,通过Attention策略增强网络对位置信息的描述。三维轨迹规划部分,设计融合特征高度的自适应分层算法,减少分层高度偏移,缩减阶梯误差;根据分层结果进行轮廓提取、填充,生成三维轨迹。结果表明,坐标匹配误差小于1mm,三维修复轨迹规划质量较高。

焊接机器人管-管相贯线焊接工艺试验研究

相贯线焊缝是工业生产中典型的焊缝形式之一。相贯线是复杂的空间曲线,采用手工焊接的方法很难保证焊接质量,而利用机器人焊接相贯线焊缝可以大大提高焊接效率和产品质量的稳定性。

基于上位机的工业机器人磨头工具坐标系自动标定技术研究

将工业机器人自动标定引入制造领域,能够在需要更换执行工具时实现快速标定,提高效率。针对目前工业机器人工具坐标系需要人工操作示教器进行标定的情况,设计了一种基于上位机的机器人磨头工具坐标系自动标定系统。该系统通过上位机软件实现对FANUC M20iA/20M工业机器人磨头工具坐标系的自动标定,包括工具中心点位置标定和工具中心点姿态标定,降低了示教器的介入,减少了标定时间。工具中心点位置标定通过四点标定法求解末端连杆坐标系位姿数据,应用最小二乘法求解磨头工具坐标系位置,采用四元数表示法降低计算量;工具中心点姿态标定保持工具坐标系位姿不变,记录不同标定点的末端连杆坐标系数据,并设计关节运动控制模块、设置坐标系模块和位姿标定线性移动模块。上位机通过Socket与机器人通信联动,发送控制指令,实现自动标定过程控制。仿真与实验结果表明,所设计标定系统能够对磨头工具坐标系实现自动高精度标定,标定精度±0.3 mm,满足实际加工需求,为后续的工业机器人磨抛加工应用奠定了基础。