Robot Motion Model Research Articles

A Study of Library Mobile Robot Book Classification and Transportation by Integrating DA and RMM

As the complexity of modern library management tasks increases, it is difficult for traditional mobile robots to meet the task of moving and classifying books. In order to design a mobile robot that can autonomously classify and transport books, the study realizes the tasks of book classification and transportation in libraries by fusing the differential speed algorithm and the robot motion model algorithm. First, the robot operating system is utilized to scan the books, classify the books, and obtain the category information of the books. Then, the differential speed algorithm is used to control the motion of the robot to ensure that the robot can accurately transport the books to the designated location. At the same time, combined with the robot motion model algorithm, the motion trajectory of the robot is planned to ensure that the robot can avoid obstacles and stably complete the book transportation task. Finally, the deep reinforcement learning algorithm is used to train the decision-making model of the robot to improve the intelligence level of the robot. The results of simulation experiments show that the research method has the highest accuracy, with an average accuracy of 99.98%, and the robot is able to accurately categorize the books and quickly avoid obstacles with strong stability. The results of the application experiments show that the research method has the shortest moving distance, with an average moving distance of 132 m and an average completion time of 34 seconds, which are lower than the remaining three types of robots. The research robot showed high accuracy in the task of returning books in four time periods within 10 days in the library, with an average accuracy of 99.58%. The experimental results validate the superiority of the research methodology and show that the robots are capable of accurately recognizing and classifying books and can autonomously perform transportation tasks in libraries. The research results help to improve the automation level and management efficiency of libraries and have important application value.

Surface hydrodynamic characteristic analysis of underwater robots applied to perception of lateral lines

Inspired by the hydrodynamic perception abilities based on lateral lines on fish surfaces, the artificial lateral lines (ALLs) based on pressure and flow sensors were proposed by the researchers. As the ALLs are widely used in underwater robots, the mechanisms of lateral line perception are urgently needed to be studied. Based on the lattice Boltzmann method, immersion boundary method, and large eddy simulation, a three-dimensional numerical model of underwater robot motion is established and verified. The distribution and variation of velocity and surface pressure on robots with different shapes under different flow fields are studied in detail. It is found that the robots with the upstream surface curvature aspect ratio of 1:1 are more suitable for placing ALLs. Then, similarly, the hydrodynamic perception abilities of robots with different sizes are further investigated. It was observed that the smaller the robot size, the better the perception ability. In addition, sensing devices are more suitable for placement on the upstream surface of the robots. These conclusions can also explain the physiological characteristics of cavefish with well-developed lateral lines in nature. Finally, based on the above analysis, to guide the shape design and sensor layout of the robots, an evaluation index for the perception ability of the robot is proposed. The reliability of the evaluation index is verified by using a machine learning method based on polynomial regression to predict the flow field. The R-square of machine learning can reach 0.99 at the upstream surface of the robot.

Tracking control of wheeled mobile robots via intermittent control.

This paper was concerned with the trajectory tracking control of wheeled mobile robots using aperiodic intermittent control. By establishing the corresponding motion model of the wheeled mobile robot, a tracking control strategy was proposed based on the intermittent control approach and backstepping method. Compared to the controllers using continuous state feedback, the proposed control strategy was activated only on separate time intervals, which combined the features of closed- and open-loop control. An example was given to illustrate the effectiveness of the obtained result.

Design of nonlinear control system for motion trajectory of industrial handling robot

AbstractIndustrial robot is a and multi‐output complex system with strong coupling and high nonlinearity. The motion control accuracy of the system is affected by many factors. To solve the difficulty in establishing the input and output characteristics of robot dynamics modeling, the robot motion model is established through the Lagrangian energy function. At the same time, the nonlinear relationship between angular velocity, angular acceleration, and robot torque is accurately expressed through improved cascaded neural network. In addition, the optimal time planning of the robot's trajectory in joint space is studied using multinomial interpolation method and the particle swarm optimization (PSO). In the simulation experiment, the effect of the proposed dynamic model fitting was outstanding. Under the mixed multinomial difference calculation planning, the angular position trajectories of the three joints changed very smoothly. In the data set application test, the average error of the PSO algorithm was 0.4061 mm and the average task time was 9.101 s, which were lower than other planning algorithms. Experiments showed that the Lagrangian dynamic model analysis based on genetic algorithm cascaded neural network and PSO trajectory scheduling method under mixed multinomial difference had better trajectory planning performance in handling tasks.

Control strategy based on improved fuzzy algorithm for energy control of wrist rehabilitation robot

With the complex changes in social and demographic structure, the problem of aging is becoming increasingly serious, and the demand for equipment in the field of medical rehabilitation is also increasing. Given the above situation, various countries have proposed using rehabilitation robots to assist patients in treatment, and have achieved certain results. The rehabilitation robot helps the injured area gradually recover autonomous movement through repeated auxiliary actions, thereby achieving the goal of physical rehabilitation training. However, most robot configurations face insufficient energy and power, as well as bulky and inflexible equipment. Based on the above issues, this article adopts an improved fuzzy algorithm control strategy to optimize the energy storage device and applies the energy system to the wrist rehabilitation training robot device. Firstly, a fuzzy adaptive algorithm is added to the traditional energy controller to combine system control with operational status, achieving precise control and dynamic adjustment of energy allocation. The research has added filter optimization design, which improves the accuracy and effectiveness of fuzzy algorithms. Finally, this article establishes an upper limb motion model of the rehabilitation robot and configures relevant hardware systems. At the same time, this article also uses manufacturing materials that meet functional requirements to construct auxiliary equipment. The results indicate that the improved fuzzy algorithm can improve the auxiliary effect in energy control of wrist rehabilitation robots. It has obvious advantages in the process of wrist rehabilitation training.

Design and Simulation of On-Orbit Assembly System Based on Insect-Inspired Transportation

In response to the requirements of large-scale space in-orbit assembly and the special environment of low gravity in space, this paper proposes a small robot structure with the integration of assembly, connection, and vibration reduction functionalities. Each robot consists of a body and three composite mechanical arms-legs, which can dock and transfer assembly units with the transport spacecraft unit, and also crawl along the edge truss of the assembly unit to a designated location to complete in-orbit assembly while ensuring precision. A theoretical model of robot motion was established for simulation studies, and in the research process, the vibration of the assembly unit was studied, and preliminary adjustments were made to address the vibration issue. The results show that this structure is feasible for in-orbit assembly schemes and has good adjustment ability for flexible vibration.

Set‐theoretic localization for mobile robots with infrastructure‐based sensing

AbstractIn this article, we propose a set‐membership based localization approach for mobile robots using infrastructure‐based sensing. Under an assumption of known uncertainties bounds of the noise in the sensor measurement and robot motion models, the proposed method computes uncertainty sets that over‐bound the robot 2D body and orientation via set‐valued motion propagation and subsequent measurement update from infrastructure‐based sensing. We establish theoretical properties and computational approaches for this set‐theoretic localization method and illustrate its application to an automated valet parking example in simulations, and to omnidirectional robot localization problems in real‐world experiments. With deteriorating uncertainties in system parameters and initialization parameters, we conduct sensitivity analysis and demonstrate that the proposed method, in comparison to the FastSLAM, has a milder performance degradation, thus is more robust against the changes in the parameters. Meanwhile, the proposed method can provide estimates with smaller standard deviation values.

Cooperative Following of Multiple Autonomous Robots Based on Consensus Estimation

When performing a specific task, a Multi-Agent System (MAS) not only needs to coordinate the whole formation but also needs to coordinate the dynamic relationship among all the agents, which means judging and adjusting their positions in the formation according to their location, velocity, surrounding obstacles and other information to accomplish specific tasks. This paper devises an integral separation feedback method for a single-agent control with a developed robot motion model; then, an enhanced strategy incorporating the dynamic information of the leader robot is proposed for further improvement. On this basis, a method of combining second-order formation control with path planning is proposed for multiple-agents following control, which uses the system dynamic of one agent and the Laplacian matrix to generate the consensus protocol. Due to a second-order consensus, the agents exchange information according to a pre-specified communication digraph and keep in a certain following formation. Moreover, an improved path planning method using an artificial potential field is developed to guide the MAS to reach the destination and avoid collisions. The effectiveness of the proposed approach is verified with simulation results in different scenarios.

Trajectory Planning using Transfer Learning and Wireless Sensor Network for Target Search Mobile Robot

Trajectory planning is the core technology in the field of mobile robot research. However, the traditional trajectory planning algorithm has the problems of low accuracy and high complexity. Therefore, we propose a trajectory planning algorithm for target search mobile robot using transfer learning (TL) and wireless sensor network. First, the mobile robot motion model is constructed and converted into a linear motion model; Second, the robot kinematic constraints such as velocity, acceleration and position are analyzed; Then, the ultrasonic sensor is constructed to sense the robot's self and environmental information, and the path planning is performed by the combination of global planning and local planning. Finally, a combination of global planning and local planning is used for path planning, and the knowledge is learned from global planning based on TL, and the relevant factors of the global planning model are applied to local planning as the initial motion state factors of the robot to realize the trajectory planning of the target-search mobile robot. The results show that the fitting of the proposed algorithm and the optimal trajectory planning results is high, the reward value of robot training is higher, the trajectory planning velocity curve is smoother, and the space complexity of the proposed algorithm is much lower than other algorithms, the highest is only 23%, and the accuracy of trajectory planning is as high as 95.6%, which has practical applicability.

Active Compliance Control System for Intelligent Inspection Robot in Power Room

In order to solve the problems of blind spot and time-consuming and laborious monitoring in manual inspection of power information and communication rooms, a kind of active compliant control system for intelligent inspection robots of power information and communication rooms is proposed. This research includes the noncontact detection method of the inspection robot in the power room based on machine vision; the optimization environment of the power room; the control of the inspection robot through the monitoring system terminal; the automatic visual inspection of the machine through the monitoring network transmission; the display of the monitoring terminal and the use of the calibration of the machine; and the edge detection method of the inspection image. The motion model of the inspection robot in the power room is constructed and the compliant control method of the inspection robot is designed. The experimental results show that the ineffective fluctuation range of torque of each joint is the smallest when the inspection robot is disturbed by obstacles in the process of executing signal change instructions, and the average fluctuation range of robot limbs is 0.65%. Conclusion. Based on the research results of this essay, it is proved that the controllability of power signal lamp change can be optimized separately in the future, and the safety of circuit operation can be improved.

Mathematical modeling and computer simulation of the wheeled vibration-driven in-pipe robot motion

The in-pipe robots are currently of significant interest, considering numerous recent publications on this subject. Such machines can use various locomotion principles: wheeled, tracked (caterpillar), walking (legged), screw-type, worm-type, snake-type, etc. In most cases, such robots are equipped with an active drive system transmitting the torque from a motor shaft to the corresponding locomotion mechanism (wheels, tracks, etc.). The present paper is devoted to the wheeled in-pipe robot that doesn’t need a complex transmission. In such a case, the idea of implementing the vibratory locomotion system driven by an internal unbalanced mass is proposed. The corresponding kinematic diagram of the wheeled vibration-driven in-pipe robot is developed, and the differential equations describing the robot motion are deduced. In order to carry out the virtual experimental investigations, the robot’s simulation model is designed in the SolidWorks software. The major scientific novelty of the present research consists in developing the theoretical foundation for designing and practical implementation of the in-pipe robots driven by the inertial vibration exciters and equipped with the unidirectionally rotating wheels and overrunning clutches. The results of numerical modeling and computer simulation of the robot motion substantiate the possibilities and expediency of implementing the proposed vibration-driven locomotion principles while creating novel designs of the in-pipe robots.

An Adsorption Robot for Pipeline Inspection of Gas Insulation Switchgear

In order to enable a robot to do the omni-directional mobility for inspection in the pipeline of Gas Insulation Switchgear, a negative pressure adsorption pipeline robot is designed. Firstly, the mechanical structure was designed for the omni-directional mobility based on the negative pressure adsorption. The internal surface motion model of the pipeline robot was built, and a variable adsorption control method was proposed by mechanical analysis. Simulations and experiments showed that the robot could steadily adsorb on any position of the pipeline, which validated the capability of omni-directional mobility for the designed robot. This robot can be used for inspection of the Gas Insulation Switchgear in electric power industry in the near future.

Design and motion analysis of a small motor stator multi-wire paralleled winding hybrid robot

Abstract. The working space of small motor stators is narrow, and most of them are manual winding. It is difficult to guarantee the uniform arrangement of enameled wires by multi-wire winding. To solve these problems, a three-phase parallel equivalent multi-wire winding robot is proposed to achieve large output torque of the motor. Firstly, according to the equivalent model, the structure of the large arm, small arm and manipulator is designed to determine the motion model of the winding robot. Euler's kinematics theory is used to analyze the change of the working position of the arm, and the rotation matrix of the arm and the constraint equation of the motion vector of each branch chain are established. The motion model of the arm and the manipulator are established using inverse kinematics and analytical analysis. The motion pose of each joint of the winding robot is studied to ensure that the robot realizes a three-phase parallel multi-wire winding motion. ADAMS software was used for kinematic simulation analysis of the winding robot. The displacement of the branch chain on the xyz axis was represented by the torque of the virtual motor to verify the correctness of the inverse kinematics solution and the closure condition of the manipulator block. Finally, the ROS simulation platform is built to simulate the joint motion planning of the winding robot to verify the multi-line parallel principle and the feasibility of the multi-line parallel winding hybrid robot. The research results of this paper provide a theoretical reference for multi-wire parallel winding equipment control.

Experimental studies and modeling of four-wheeled mobile robot motion taking into account wheel slippage

Experimental studies and modeling of four-wheeled mobile robot motion taking into account wheel slippage

Research on intelligent mobile robot full coverage path planning

Aiming at the full coverage path planning problem of intelligent robot, a local chaos evaluation planning method is proposed. Considering the randomness and unpredictability of the mobile robot, a four-dimensional chaotic system with feedback control variables is designed. The path planning model is established by fusing the system with the robot motion model. At the same time, the coupling control parameters are introduced to adjust the system error. According to the initial coordinates and chaotic initial state parameters of the robot, the moving path points can be calculated by differential discretization. Considering the local optimal solution of the path planning, the mobile space of the robot is meshed, and the dynamic mesh activity value is calculated according to the excitation. The mesh activity is used to divide the mobile path planning, and then the local path and angular displacement changes are obtained. At the same time, the corresponding index evaluation is designed for local path planning to correct the planning results. The simulation results show that the proposed local chaos evaluation planning method has a good effect of full path coverage, and obtains lower path repetition rate, moving distance and path planning time, which effectively improves the mobile efficiency and control stability of the robot.

Design and Passive Training Control of Elbow Rehabilitation Robot

In this paper, a rehabilitation robot driven by multifilament muscles is designed based on the rehabilitation robot motion model and a system elbow joint model. The passive training mode of rehabilitation robots were researched, and active disturbance rejection control (ADRC) leveraged to improve the tracking angle of robot joints. In the no-load motion simulation of rehabilitation robots, disturbances are added to the control variables to complete the ADRC and Proportional Integral Differential (PID) position control simulation. The simulation results indicate that the auto disturbance rejection control can quickly keep up the expected signal without overshoot, solve the contradiction between the system rapidity and overshoot. Moreover, it can better suppress the interference even if the external load changes. The upper limbs of the human body are used as the load on the robot body to complete the simulation of ADRC and PID position control objects of different weights. Finally, a passive rehabilitation training experiment was conducted to verify the safety of the rehabilitation robot, the rationality, comfort, and robustness of the mechanism design, and the effectiveness and feasibility of the ADRC.

Structural Dynamics Simulation Analysis of Industrial Robot Arm Based on Kane Method

When the traditional methods are used to analyze the dynamics of the robot arm structure, the stability of the arm structure is not good and the simulation effect of the operation process is not good. For this reason, Kane method is introduced in this paper to carry out dynamic simulation analysis of industrial robot arm structure. The operating process of the industrial robot arm structure was simulated by Kane method, and the angular acceleration of the robot’s main arm, forearm and push rod was solved in each cycle. The Jacobian matrix of the 5 degree of freedom manipulator joint is established, the singular configuration of each joint is calculated, and multiple joint variable combinations are generated by random number. The forward motion equation of the robot endpoint set was solved to obtain the endpoint set of the robot. The Lagrangian method was used to model the robot with Kane 3D simulation software to simulate and analyze the dynamic process of the driving torque required to grab the mass workpiece at the three joints. The joint motion model of robot is established on ADAMS simulation software, and the torque curve of the rotating joint of industrial robot arm structure is obtained. MATLAB simulation software is used for simulation. The results show that the integrated design method of manipulator and machine tool is correct, which provides a comprehensive data basis for the selection of servo motor.

Kinematics Analysis and Trajectory Planning of Segmentation Robot for Chilled Sheep Carcass

HighlightsAn automatic sheep segmentation robot system was developed to realize the automatic segmentation of chilled sheep carcass and improve the segmentation efficiency.The mechanical properties of mutton and lamb ribs were analyzed.The motion model of robot was established and the cutting path of sheep carcass was designed.Accurate segmentation of sheep carcass was realized.Abstract. With the quick development of animal husbandry, it is imperative to switch from extensive management to intensive operation. To improve the automation and quality of mutton segmentation, an automatic sheep segmentation robot system was developed in this article, which realizes the automatic segmentation of chilled sheep carcass and improves the segmentation efficiency of chilled sheep carcass. According to the technological requirements of sheep carcass segmentation, the cutting procedure of slaughtering chilled fresh sheep carcass was designed and the three-dimensional model of chilled fresh sheep carcass was established in reverse. A chilled fresh sheep carcass clamp was designed based on the characteristics of the profiling structure. Then the mechanical characteristics of chilled fresh mutton and sheep ribs were analyzed. Specifically, considering that the carcass of chilled fresh sheep is a viscous body, the shear test of chilled fresh mutton tissue was carried out. Thus, the kinematics model of segmentation robot was established. The workspace of the slaughtering robot was analyzed. Furthermore, the dynamic model of a slaughtering robot was established. The cutting track of the segmentation robot was designed and the sheep carcass cutting experiment was completed on the segmentation robot system. The mass of sheep carcass before and after cutting were 15.3 and 14.9 kg, respectively. The loss rate during cutting was 2.61%, which indicates the incision was smooth and the sheep carcass segmentation was accurate. The effectiveness of the sheep carcass segmentation robot was proved by experimental results. Keywords: Cutting force, Reverse modeling, Sheep contour, Segmentation robot, Trajectory planning.

Research on robot optimal path planning method based on improved ant colony algorithm

To overcome the problem of poor convergence and obstacle avoidance when traditional methods are used to plan the optimal path of robot, a new optimal path planning method based on improved ant colony algorithm is proposed. Firstly, the odometer model, ultrasonic sensor model and robot motion model are constructed to obtain the environmental information and robot motion state information. Then, according to the adaptive transformation heuristic function of the target point and the principle of wolf swarm assignment, the pheromone is refreshed. On this basis, the core parameters of the improved ant colony algorithm are optimised by particle swarm algorithm, so as to complete the optimal path planning of the robot. The experimental results show that the overall mean value of collision avoidance of the proposed method is 0.97, and the planning performance is significantly better than that of similar planning methods, with considerable application value.

Fully Distributed Joint Localization and Target Tracking With Mobile Robot Networks

In this article, we study the problem of joint localization and target tracking using a mobile robot network. Here, a team of mobile robots equipped with onboard sensors simultaneously localize themselves and track multiple targets. We introduce a fully distributed algorithm that is applicable to generic robot motion, target process, and measurement models and is robust to time-varying sensing and communication topologies and changing blind robots (the robots not directly sensing the targets). Instead of treating localization and target tracking as two separate problems, we explicitly account for the influence of one to the other and exploit it to improve performance in a fully distributed context. Two novel kinds of distributed estimates are derived. By employing them, each robot can estimate the pose (position and orientation) of itself (localization) and the states of targets (tracking) using only its local information and information from its one-hop communicating neighbors while preserving consistency. Furthermore, it is proven that, in the case of linear time-varying models, the estimation errors are bounded in the mean-square sense under very mild conditions on the sensing and communication graph and system observability. The effectiveness of our approach is demonstrated extensively through Monte Carlo simulations, and experiments carried out using a real-world data set. It is also shown better performance in the pose estimates of the robots is achieved when jointly estimating the robots' poses and targets' states.