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• A novel redundantly actuated series-parallel manipulator is proposed. • Unified recursive kinematics and statics models of the manipulator are established. • The theoretical model is validated by comprehensive numerical results. • Load/mass ratio of the tested manipulator in non-redundant actuation mode is 1.34. • The manipulator has higher load-carrying capacity in redundant actuation mode. Construction robots with mobile systems are an integral part of automatic building processes. However, with the vigorous development of prefabricated buildings, traditional manipulators have progressively failed to satisfy the requirements of handling heavy materials on construction sites. Thus, this paper proposes a redundantly actuated series-parallel manipulator (RAS-PM). To explore the feasibility of applying the manipulator in construction tasks, this paper establishes the unified recursive kinematics and statics of the manipulator and verifies the validity and reliability of the theoretical modeling method through comprehensive numerical results. The prototype of the manipulator is developed and installed on a bionic hexapod construction robot. The test results demonstrate that the manipulator exhibits an excellent load/mass ratio in non-redundant actuation mode, and its load-carrying capacity can be further enhanced with the optimized force/position hybrid actuation. In the on-site test, the robot can freely switch between modes to handle horizontal and vertical states of materials, such as curtain walls and large panels, thereby contributing to modern prefabricated construction. [ABSTRACT FROM AUTHOR]

• A mathematical model for inverse kinematics and shape modeling of continuum robots is presented. • The inverse kinematics algorithm performs very well in the accuracy and efficiency by simulation. • Shape modeling of continuum robots is verified by prototype experiment. A mathematical model for the inverse kinematics and shape modeling of continuum robots is presented in this paper. This method simplifies the forward kinematics derivation process by introducing a rotation axis. In the inverse kinematics solution, an iterative approach is employed to try different initial values, and the optimal initial value is obtained by computing the condition number of the Jacobian matrix. Simulation experiments are verified that optimized initial values can effectively enhance the efficiency of inverse kinematics solution. Based on the Euler-Bernoulli beam theory, the shape modeling of continuum robots is derived, and the mathematical model of the relationship between robot shape and end loads is established. Finally, the mathematical model is verified through prototype experiments, demonstrating that the established shape modeling can achieve accurate simulation of deformation within a range where the bending angle is less than 90°, with errors within 10 %. [ABSTRACT FROM AUTHOR]

In the engineering practice of performing robotic measurements with a 2D scanner, a major difficulty is to accurately determine the tool center point (TCP) quickly and easily since it does not exist as a physical object. The article proposes an algorithm for determining the coordinates of the TCP point. It relies on the possibility of using a conical element, such as a milling cutter of unknown geometry. So far, the algorithms found in the literature were based on a sphere of known size. The presented solution was simulated in RobotStudio 2019 software, while calculations were performed in Maple 14 software. In addition, the correctness of the presented solutions was verified on a real object, an IRB 2400 robot equipped with a Keyence 2D scanner. [ABSTRACT FROM AUTHOR]

The article deals with the design of the educational model of the robot, where, in addition to kinematics, the control system of the robot and the simulation of the robot's activity in the GAZEBO environment are also addressed. Students can train different control algorithms on this model. At the same time, a graphical interface for simulating the robot's activity is also created. The control system is composed of a low-cost embedded Arduino system, which is very easy to program and create control systems. Simulations and experiments showed the correctness of the design methodology of such a robot model. [ABSTRACT FROM AUTHOR]

This paper presents a novel parallel manipulator capable of generating two translations (2T), inside a vertical plane, and two rotations (2R), about horizontal axes, which are required in aerospace, manufacturing and rehabilitation fields. These four degrees of freedom are reached by means of a unique RRU and three RSS kinematic chains connected to a rhomboid-shaped mobile platform. The kinematic analysis of the new manipulator is provided, which includes the resolution of the inverse position problem and the velocity equations relating to input and output variables. Additionally, a methodology is proposed for obtaining the workspace free of singularities, collisions and kinematic joint range limitation. This systematic methodology allows designers to identify the critical factors affecting the workspace and, thus, to rearrange the mechanical design accordingly for optimum path planning. We represent the workspace using its two-dimensional subspaces (i.e., translational and rotational workspace). The results are analyzed for different working modes of the manipulator to see its potential use in applications wherein 2T2R motion is necessary. [ABSTRACT FROM AUTHOR]

The forward kinematics of a general six-degree-of-freedom parallel mechanism is a significant challenge in mechanism theory, following the displacement analysis of spatial 7R (R: revolute joint) mechanisms. Currently, there is no comprehensive analytical solution available. Using the zero-coupling “3-2-1” Stewart-type parallel robot as an example, this study investigates the number of solutions for the forward kinematics and analyzes the conditions under which the number of solutions varies. First, based on the rod length constraint equations and applying the tetrahedron principle, all eight sets of solutions for the robot’s forward kinematics are analytically derived. Then, by examining the positional characteristics of the moving spherical joints, the mathematical conditions required for the solution equations to yield 8, 4, 2, or 1 analytical solutions are identified. Furthermore, by considering the positional characteristics of the fixed spherical joints and integrating the forward kinematics algorithm, the factors influencing the number of real solutions are explored. Finally, the intrinsic relationship between the number of solutions to the forward kinematics of the parallel robot and Hunt’s singularities is analyzed. The findings of this research provide a theoretical foundation for the real-time control and trajectory planning of parallel robots. [ABSTRACT FROM AUTHOR]

How to quickly and accurately identify the kinematic parameter errors is an important prerequisite for robot accuracy compensation. The laser tracker is used to measure and identify the kinematic parameters of the robot. The influence of laser tracker layout in robot pose measurement is analyzed, and the evaluation function of laser tracker layout is constructed to determine the optimal layout position. Then, the mapping relationship between the position and orientation deviation of the robot end and the deviation of each kinematic parameter is established, and the kinematic parameter identification model integrating the position and orientation information is constructed. The identification model is compared to the identification model based on position information to clarify the intrinsic reason of high accuracy. Next, aiming at the problem that the genetic algorithm is easy to prematurely converge to the local optimal solution, a hybrid genetic algorithm is constructed by introducing the simplex method to determine the optimal calibration pose set of the robot. On this basis, the results of robot kinematics parameter identification based on position measurement data, pose measurement data, and optimal calibration pose set are compared and analyzed through experiments, which verifies the effectiveness of the robot kinematics parameter identification model based on pose measurement data and optimization strategy. [ABSTRACT FROM AUTHOR]

The inverse kinematics of robotic manipulators involves determining an appropriate joint configuration to achieve a specified end-effector position. This problem is challenging because the inverse kinematics of manipulators are highly nonlinear and complexly coupled. To address this challenge, the bald eagle search optimization algorithm is introduced. This algorithm combines the advantages of evolutionary and swarm techniques, making it more effective at solving nonlinear problems and improving search efficiency. Due to the tendency of the algorithm to fall into local optima, the Lévy flight strategy is introduced to enhance its performance. This strategy adopts a heavy-tailed distribution to generate long-distance jumps, thereby preventing the algorithm from becoming trapped in local optima and enhancing its global search efficiency. The experiments first evaluated the accuracy and robustness of the proposed algorithm based on the inverse kinematics problem of manipulators, achieving a solution accuracy of up to 10 − 18 m. Subsequently, the proposed algorithm was compared with other algorithms using the CEC2017 test functions. The results showed that the improved algorithm significantly outperformed the original in accuracy, convergence speed, and stability. Specifically, it achieved over 70% improvement in both standard deviation and mean for several test functions, demonstrating the effectiveness of the Lévy flight strategy in enhancing global search capabilities. Furthermore, the practicality of the proposed algorithm was verified through two real engineering optimization problems. [ABSTRACT FROM AUTHOR]

Robot manipulators play a critical role in several industrial applications by providing high precision and accuracy. To perform these tasks, manipulator robots require the effective computation of inverse kinematics. Conventional methods to solve IK often encounter significant challenges, such as singularities, non-linear equations, and poor generalization across different robotic configurations. In this work, we propose a novel approach to solve the inverse kinematics (IK) problem in robotic manipulators using a metaheuristic algorithm enhanced with a Jacobian step. Our method overcomes those limitations by selectively applying the Jacobian step to the differential evolution (DE) algorithm. The effectiveness and versatility of the proposed approach are demonstrated through simulations and real-world experimentation on a 5 DOF KUKA robotic arm. [ABSTRACT FROM AUTHOR]

In this study, task space tracking control of robot manipulators driven by brushless DC (BLDC) motors is considered. Dynamics of actuators are taken into account and the entire electromechanical system (i.e. kinematic, dynamic, and electrical models) is assumed to include parametric/structured uncertainties. A novel adaptive controller is designed and the stability of the closed loop system is ensured via novel Lyapunov type tools. To demonstrate performance and applicability of the proposed method, a simulation study is conducted using the model of a two degree of freedom, planar robotic manipulator driven by BLDC motors. [ABSTRACT FROM AUTHOR]

Redundant degree-of-freedom (DOF) manipulators offer increased flexibility and are better suited for obstacle avoidance, yet precise control of these systems remains a significant challenge. This paper addresses the issues of slow training convergence and suboptimal stability that plague current deep reinforcement learning (DRL)-based control strategies for redundant DOF manipulators. We propose a novel DRL-based intelligent control strategy, FK-DRL, which integrates the manipulator's forward kinematics (FK) model into the control framework. Initially, we conceptualize the control task as a Markov decision process (MDP) and construct the FK model for the manipulator. Subsequently, we expound on the integration principles and training procedures for amalgamating the FK model with existing DRL algorithms. Our experimental analysis, applied to 7-DOF and 4-DOF manipulators in simulated and real-world environments, evaluates the FK-DRL strategy's performance. The results indicate that compared to classical DRL algorithms, the FK-DDPG, FK-TD3, and FK-SAC algorithms improved the success rates of intelligent control tasks for the 7-DOF manipulator by 21%, 87%, and 64%, respectively, and the training convergence speeds increased by 21%, 18%, and 68%, respectively. These outcomes validate the proposed algorithm's effectiveness and advantages in redundant manipulator control using DRL and FK models. [ABSTRACT FROM AUTHOR]

Continuum robots are flexible and compliant. Compared to the case in conventional articulated manipulators, the driving unit can be placed outside the workspace of the robot, so that the motion orientation has a relatively complete linear configuration flow, which can be applied to a special environment with narrow and multiple obstacles such as aerospace. This study presents the development process of a tendon-driven continuum robot (TCR) with a high length-diameter ratio. The skeleton structure which imitates a snake is composed of continuous joints in series. The driving device is operated by using a tendon-driven method, which reduces the complexity of the driving box and control system significantly. The diameter of the robot is designed to be 5 mm, which enables it to work in a narrow and slender space with certain flexibility. Subsequently, a kinematic model of the robot is established. The mode function backbone method is applied to realize TCR trajectory planning. An idea of segmented solving is adopted to achieve trajectory tracking control of the continuum robot. Finally, a prototype of the continuum robot is produced, and the rationality of the robot design and the effectiveness of the motion control method are verified through trajectory simulations and experiments. The robot can perform inspection tasks within a narrow gap of 20 mm with good environmental adaptability. [ABSTRACT FROM AUTHOR]

In recent years, the development of robots for agro-industrial applications, such as the cultivation of Solanum tuberosum potatoes, has aroused the interest of the academic and scientific communities. This is due, at least in part, to the complexity of modeling and robustly controlling some dynamics inherent to nonlinear behaviors normally attributed to the different technologies associated with the movement of these autonomous vehicles and their nonholonomic constraints. The different nonlinear dynamics of mobile robots are usually represented by state-space models. However, given some equilibrium and stability characteristics, the implementation of effective controllers for the robust parametric tracking and variation problem requires techniques that allow the operability of robots around regions of stable equilibrium. Feedback linearization control is one such technique that attempts to mathematically eliminate nonlinear expressions from the plant model. However, this technique requires an observable and controllable mathematical model. If there is some relationship between the model inputs and a controlled output that allows the relative degree of the control law to be determined, the controller design and implementation are posed as a linear issue. Flat filters developed from the generalized proportional integral control approach are an alternative that could facilitate the design of controllers for these linearized systems. From these flat filters, it is possible to obtain the transfer function of a controller without relying on the derivatives of the system output. This work proposes the design of a controller via exact linearization and its equivalent flat filter for a robot inspector of the soil resource of S. tuberosum crops in the department of Cundinamarca, Colombia. The actuator motion constraints resulted in a robot with two degrees of mobility and one non-holonomic constraint. Numerical validation of this system suggests that it can be an effective solution to the problem of tracking control at changing references by providing a system capable of navigating through crop rows. The results suggest correct tracking for linear and circular trajectories. However, the control lacks the ability to track spiral-type trajectories. [ABSTRACT FROM AUTHOR]

This paper presents a tangleand contact-free path planning (TCFPP) for a mobile robot attached to a base station with a finite-length cable. This type of robot, called a tethered mobile robot, can endure long-time exploration with a continuous power supply and stable communication via its cable. However, the robot faces potential hazards that endanger its operation such as cable snagging on and cable entanglement with obstacles and the robot. To address these challenges, our approach incorporates homotopy-aware path planning into deep reinforcement learning. The proposed reward design in the learning problem penalizes the cable-obstacle and cable-robot contacts and encourages the robot to follow the homotopy-aware path toward a goal. We consider two distinct scenarios for the initial cable configuration: 1) the robot pulls the cable sequentially from the base while heading for the goal, and 2) the robot moves to the goal starting from a state where the cable has already been partially deployed. The proposed method is compared with naive approaches in terms of contact avoidance and path similarity. Simulation results revealed that the robot can successfully find a contact-minimized path under the guidance of the reference path in both scenarios. [ABSTRACT FROM AUTHOR]

Hexapod robots have gained significant attention due to their potential applications in complex terrains and dynamic environments. However, traditional inverse kinematics approaches often face challenges in meeting the precision required for adaptive omnidirectional movement. This work introduces a novel approach to addressing these challenges through the Directed Angular Restitution (DAR) method. The DAR method offers significant innovation by simplifying the calculation of rotational transformations necessary for aligning vectors across different planes, thus enhancing control, stability, and accuracy in robotic applications. Unlike conventional methods, the DAR method extends the range of trigonometric functions and incorporates spin functions to ensure continuous and smooth trajectory tracking. This innovative approach has been rigorously tested on a hexapod robot model, demonstrating superior performance in movement precision and stability. The results confirm that the DAR method provides a robust and scalable solution for the inverse kinematics of hexapod robots, making it a critical advancement for applications in robotics and automation where precise control and adaptability are paramount. [ABSTRACT FROM AUTHOR]

In recent years, the remote center of motion (RCM) constraint has moved from purely mechanical to software implementation, enabling the use of serial manipulators in robotic‐assisted minimal invasive surgery. However, ensuring safety with software‐based RCM presents challenges. This article addresses this issue by introducing a novel control algorithm for a 7‐DOF redundant robotic arm, taking into account a software RCM while considering system passivity and kinematic constraints. The algorithm is both a control optimizer and a robot kinematics inversion, enabling precise and dexterous control for various surgical tasks and other control applications. By formulating a quadratic optimization problem under linear constraints, the algorithm guarantees the robotic arm's performance, safety, and stability under communication delay. Experimental validation demonstrates the effectiveness and accuracy of the control algorithm in executing a surgical training task (peg‐and‐ring) during bilateral teleoperation. The results highlight the successful implementation of the RCM constraint, ensuring patient safety and optimizing the manipulation capabilities of the robotic arm. [ABSTRACT FROM AUTHOR]

This study explores the development and implementation of Shadow, an advanced mobile social robot designed to meet specific functional requirements. Shadow is intended to serve both as a versatile tool and a human companion, assisting in various tasks across different environments. The construction emphasizes cost efficiency and high agility, utilizing 3D printing technology exclusively. The robot features omnidirectional kinematics and a flexible power electronics system, accommodating diverse energy needs with lithium batteries that ensure at least seven hours of autonomous operation. An integrated sensor array continuously monitors the power system, tracks tilt and acceleration, and facilitates self-diagnostic functions. Rapid prototyping allows for swift iteration, testing, and refinement to align with project goals. This paper provides a comprehensive blueprint for designing cost-effective, highly agile robots using advanced manufacturing techniques. Extensive testing, including stability and sensory skills evaluations, demonstrates Shadow's adherence to its design objectives. Shadow has advanced from technology readiness level (TRL) 2 to TRL 7 within a year and is currently undergoing trials with advanced functionalities, offering significant insights into overcoming practical design challenges and optimizing robot functionality. [ABSTRACT FROM AUTHOR]

The trajectory tracking is important to make the WMR move autonomously from the starting point to the destination along a predefined time. Implementing of trajectory tracking control is a fundamental part to accomplish its application tasks. In this article a new method by using a hybrid controller has been presented to solve the problem of the trajectory tracking of four mecanum wheeled mobile robot. Proposed controller is depending on modeling of robot kinematic and dynamic equations. The novelty in this work is that, an optimal control system self-tuning parameters based on an optimization algorithm for these models of the mobile robot is utilized. The optimal control type that is used in this work is the Linear Quadratic Regulator (LQR) controller. LQR is used to control the actuator torque that is required in each wheel to achieve the robot task. The parameters of the LQR controller are tuned by using Ant Colony Optimization (ACO). For results simulation, MATLAB/Simulink is used for circular and infinity shape trajectories. Results show that when the robot follows a circular trajectory, the values of position trajectory error values are reduced to small value (ex=3.218 *10-5m) and (ey= 2.224*10-5m) in xo and yo directions, respectively and remained almost at these values until the end of the simulation time. The maximum orientation error is (eθ= 0.103rad), and convergent to zero after two seconds of the mobile robot movement. Also when the robot follows an infinity shape trajectory, the position trajectory error values are (ey) and (eθ) are reduced to small value - 4.078 *10-4m and 3.174*10-4rad respectively, while, (ex) is reduced to 5.263*10-4 m after about 15 seconds. [ABSTRACT FROM AUTHOR]

Programming for swarm robots is challenging due to platform diversity and the gap between individual and swarm behaviors. To tackle this challenge, we propose a component-based software synthesis method from a high-level specification. To support heterogeneous robots and maximize code reuse, we adopt a component-based approach that classifies software components into three categories: 1) robot; 2) algorithm; and 3) consensus. We generate a task graph model for an individual robot from a high-level specification and use a software synthesizer to generate the target code from the task graph model. Through a proof-of-concept implementation with a group searching application, the viability of the proposed technique is demonstrated. [ABSTRACT FROM AUTHOR]

Abstract Herein, a control system and a fault tolerance method for the rotor positionable quadrotor are proposed. Quadrotors that have a variable structure are made for different purposes. The rotor‐positionable quadrotor studied here, is a type of drone with a variable structure that has the ability to change the position of its rotors linearly along the axis of each arm. It can be seen that this capability can improve the drone robustness against disturbances and faults in comparison with regular quadcopters. Due to the over‐actuated dynamics of this type of quadrotor, the control allocation scheme based on log‐barrier optimization is employed to obtain the position and speed of each rotor. In this study, it is experimentally shown that rotor positioning not only reduces power consumption but also increases roll and pitch control inputs magnitude. Furthermore, when a fault occurs as a decrease in rotor speed, a fuzzy method is proposed to position the rotors which tolerates the fault. Finally, numerical simulations and experimental tests verified that rotor positioning can bring more robustness, reduction in power consumption, and fault tolerance in some rotor faults capabilities for quadrotors.

This paper proposes a calculation method for the optimal solution of the inverse kinematics of redundant robots. Specifically, eight sets of vector solutions of redundant robots are solved by the D-H parameter method. Then, an objective function is designed to measure the accuracy of the robot's inverse kinematics solution and the smoothness of the robot's joint motion. By adjusting the weights of each item, the optimal solution that meets different requirements can be selected. In addition, this paper also introduces an improved artificial potential field method to solve the problem of discontinuous changes in gravitational potential in path planning and the problem of excessive joint torque caused by excessive gravitational potential. Finally, the application of the rapidly exploring random tree (RRT) algorithm in robot path planning and obstacle avoidance is introduced. The above-mentioned calculation method and path planning algorithm were verified in the joint simulation environment of MATLAB Robot Toolbox and CoppeliaSim. The proposed inverse solution method is compared with the inverse solution generated in the CoppeliaSim simulation environment, and the angle error of each joint is less than 0.01 rad. [ABSTRACT FROM AUTHOR]

This paper presents a wrist exoskeleton called the KIST Upper-Limb EXoskeleton (KULEX)-wrist for activities of daily living assistance of the elderly and the disabled. A novel linkage-based structure of the rotational mechanism with three degrees-of-freedom is proposed. The proposed wrist mechanism is composed of two prismatic-universal-spherical serial chains and one revolute-revolute-revolute spherical chain. Besides, a combination of a planar slider-crank and spherical four-bar linkages was employed as a drive mechanism for power transmission. Kinematic analysis was conducted to understand its working principle. Then, the dimensions of all the linkages were synthesized to meet the structural design suitable for the wearable exoskeleton and the transmission quality. In addition, motion twists and wrenches were geometrically derived. Finally, a prototype of the KULEX-wrist was designed, and then its performance of mechanical stiffness, motion capability, and power assistance was verified. [ABSTRACT FROM AUTHOR]

Continuum robots, possessing great flexibility, can accomplish tasks in complex work scenes, regarded as an important direction in robotics. However, the current continuum robots are not satisfying enough in terms of fabrication and maintenance, and their workspace is limited by structure and other aspects. In this paper, to address the above problems, a modular deployable robot, which adopts an origami structure instead of a flexible hinge, is proposed. A fabrication method is innovated, the Spherical Linkage Parallel Mechanism (SLPM) unit is optimized, and the installation and fabrication process of the robot is simplified through modularization. The forward kinematics and inverse kinematics of the robot and its workspace are analyzed by using the screw theory. The prototype of the robot is constructed, and its folding performance, bending performance, and motion accuracy are tested, and the error analysis and compensation optimization are carried out. After the optimization, the position error of the robot is reduced by about 65%, and the standard deviation is greatly lowered, which effectively improves the motion accuracy and stability of the robot. [ABSTRACT FROM AUTHOR]

This paper presents the computational design, fabrication, and control of a novel 3-degrees-of-freedom (DOF) soft parallel robot. The design is inspired by a delta robot structure. It is engineered to overcome the limitations of traditional soft serial robot arms, which are typically low in structural stiffness and blocking force. Soft robotic systems are becoming increasingly popular due to their inherent compliance match to that of human body, making them an efficient solution for applications requiring direct contact with humans. The proposed soft robot consists of three soft closed-loop kinematic chains, each of which includes a soft actuator and a compliant four-bar arm. The complex nonlinear dynamics of the soft robot are numerically modeled, and the model is validated experimentally using a 6-DOF electromagnetic position sensor. This research contributes to the growing body of literature in the field of soft robotics, providing insights into the computational design, fabrication, and control of soft parallel robots for use in a variety of complex applications. [ABSTRACT FROM AUTHOR]

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Redundant manipulators are universally employed to save manpower and improve work efficiency in numerous areas. Nevertheless, the redundancy makes the inverse kinematics of manipulators hard to address, thus increasing the difficulty in instructing manipulators to perform a given task. To deal with this problem, an online learning fuzzy echo state network (OLFESN) is proposed in the first place, which is based upon an online learning echo state network and the Takagi-Sugeno-Kang fuzzy inference system (FIS). Then, an OLFESN-based control scheme is devised to implement the efficient control of redundant manipulators. Furthermore, simulations and experiments on redundant manipulators, covering UR5 and Franka Emika Pandamanipulators, are carried out to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Robotics includes complex mathematical calculations and coordinate transformations in forward and inverse kinematics, path planning, and robot dynamics. Students may experience a high cognitive load and lose learning motivation because robotics can be complex and challenging to understand. This study applied virtual reality (VR) technology in robotics education to simplify and visualize complex robot kinematics, aiming to increase learning motivation and reduce cognitive load. This study incorporated real and virtual robot control to develop an integrated robot learning system. This system enables learners to control the digital twin of a physical robot and observe the synchronized motion of both the virtual and physical robots. Users can operate the virtual robot to achieve the target position by setting joint parameters or using values calculated from inverse kinematics. They can also understand the principle of digital twins by observing the synchronous motion of both robots. A teaching experiment was conducted to explore the performance of applying VR in robotics education and its impacts on cognitive load and learning motivation. The system was improved based on user responses to facilitate subsequent promotional activities. VR can transform complex robotics into easily understandable learning experiences and provide an interactive user interface, making the system a suitable learning tool for STEM education. [ABSTRACT FROM AUTHOR]

This paper introduces an autonomous robot designed for in-pipe structural health monitoring of oil/gas pipelines. This system employs a 3D Optical Laser Scanning Technical Vision System (TVS) to continuously scan the internal surface of the pipeline. This paper elaborates on the mathematical methodology of 3D laser surface scanning based on dynamic triangulation. This paper presents the mathematical framework governing the combined kinematics of the Mobile Robot (MR) and TVS. It discusses the custom design of the MR, adjusting it to use of robustized mathematics, and incorporating a laser scanner produced using a 3D printer. Both experimental and theoretical approaches are utilized to illustrate the formation of point clouds during surface scanning. This paper details the application of the simple and robust mathematical algorithm RANSAC for the preliminary processing of the measured point clouds. Furthermore, it contributes two distinct and simplified criteria for detecting defects in pipelines, specifically tailored for computer processing. In conclusion, this paper assesses the effectiveness of the proposed mathematical and physical method through experimental tests conducted under varying light conditions. [ABSTRACT FROM AUTHOR]

This paper presents an efficient inverse kinematics solution for redundant robotic arms. The proposed method combines the principles of continuation methods, improves the instability of the computation time by increasing the convergence of the kinematics function, and improves the efficiency of traditional numerical methods. The effectiveness and efficient performance of the method are demonstrated through comparative experiments. The computational speed of the method is twice as fast as the Newton–Raphson method under joint limit constraints and equal solution accuracy. [ABSTRACT FROM AUTHOR]

The redundant manipulators have more DOFs (degree of freedoms) than it requires to perform specified task. The inverse kinematic (IK) of such robots are complex and high nonlinear with multiple solutions and singularities. As such, modern Artificial Intelligence (AI) techniques have been used to address these problems. This study proposed two AI techniques based on Neural Network Genetic Algorithm (NNGA) and Particle Swarm Optimization (PSO) algorithm to solve the inverse kinematics (IK) problem of 3DOF redundant robot arm. Firstly, the forward kinematics for 3 DOF redundant manipulator has been established. Secondly, the proposed schemes based on NNGA and PSO algorithm have been presented and discussed for solving the inverse kinematics of the suggested robot. Thirdly, numerical simulations have been implemented to verify the effectiveness of the proposed methods. Three scenarios based on triangle, circular, and sine-wave trajectories have been used to evaluate the performances of the proposed techniques in terms of accuracy measure. A comparison study in performance has been conducted and the simulated results showed that the PSO algorithm gives 7% improvement compared to NNGA technique for triangle trajectory, while 2% improvement has been achieved by the PSO algorithm for circular and sine-wave trajectories. [ABSTRACT FROM AUTHOR]

Path planning is the core problem of orchard fertilization robots during their operation. The traditional full-coverage job path planning algorithm has problems, such as being not smooth enough and having a large curvature fluctuation, that lead to unsteady running and low working efficiency of robot trajectory tracking. To solve the above problems, an improved A* path planning algorithm based on a multi-constraint Bessel curve is proposed. First, by improving the traditional A* algorithm, the orchard operation path can be fully covered by adding guide points. Second, according to the differential vehicle kinematics model of the orchard fertilization robot, the robot kinematics constraint is combined with a Bessel curve to smooth the turning path of the A* algorithm, and the global path meeting the driving requirements of the orchard fertilization robot is generated by comprehensively considering multiple constraints such as the minimum turning radius and continuous curvature. Finally, the pure tracking algorithm is used to carry out tracking experiments to verify the robot's driving accuracy. The simulation and experimental results show that the maximum curvature of the planned trajectory is 0.67, which meets the autonomous operation requirements of the orchard fertilization robot. When tracking the linear path in the fertilization area, the average transverse deviation is 0.0157 m, and the maximum transverse deviation is 0.0457 m. When tracking the U-turn path, the average absolute transverse deviation is 0.1081 m, and the maximum transverse deviation is 0.1768 m, which meets the autonomous operation requirements of orchard fertilization robots. [ABSTRACT FROM AUTHOR]

Since conventional PID (Proportional–Integral–Derivative) controllers hardly control the robot to stabilize for constant force grinding under changing environmental conditions, it is necessary to add a compensation term to conventional PID controllers. An optimal parameter finding algorithm based on SAC (Soft-Actor-Critic) is proposed to solve the problem that the compensation term parameters are difficult to obtain, including training state action and normalization preprocessing, reward function design, and targeted deep neural network design. The algorithm is used to find the optimal controller compensation term parameters and applied to the PID controller to complete the compensation through the inverse kinematics of the robot to achieve constant force grinding control. To verify the algorithm's feasibility, a simulation model of a grinding robot with sensible force information is established, and the simulation results show that the controller trained with the algorithm can achieve constant force grinding of the robot. Finally, the robot constant force grinding experimental system platform is built for testing, which verifies the control effect of the optimal parameter finding algorithm on the robot constant force grinding and has specific environmental adaptability. [ABSTRACT FROM AUTHOR]

Tactile servoing is an important technique because it enables robots to manipulate objects with precision and accuracy while adapting to changes in their environments in real-time. One approach for tactile servo control with high-resolution soft tactile sensors is to estimate the contact pose relative to an object surface using a convolutional neural network (CNN) for use as a feedback signal. In this paper, we investigate how the surface pose estimation model can be extended to include shear, and utilise these combined pose-and-shear models to develop a tactile robotic system that can be programmed for diverse non-prehensile manipulation tasks, such as object tracking, surface-following, single-arm object pushing and dual-arm object pushing. In doing this, two technical challenges had to be overcome. Firstly, the use of tactile data that includes shear-induced slippage can lead to error-prone estimates unsuitable for accurate control, and so we modified the CNN into a Gaussian-density neural network and used a discriminative Bayesian filter to improve the predictions with a state dynamics model that utilises the robot kinematics. Secondly, to achieve smooth robot motion in 3D space while interacting with objects, we used SE (3) velocity-based servo control, which required re-deriving the Bayesian filter update equations using Lie group theory, as many standard assumptions do not hold for state variables defined on non-Euclidean manifolds. In future, we believe that pose-and-shear-based tactile servoing will enable many object manipulation tasks and the fully-dexterous utilisation of multi-fingered tactile robot hands. [ABSTRACT FROM AUTHOR]

Collision avoidance presents a challenging problem for multi-segment continuum robots owing to their flexible structure, limited workspaces, and restricted visual feedback, particularly when they are used in teleoperated minimally invasive surgery. This study proposes a comprehensive control framework that allows these continuum robots to automatically avoid collision and self-collision without interfering with the surgeon's control of the end effector's movement. The framework implements the early detection of collisions and active avoidance strategies by expressing the body geometry of the multi-segment continuum robot and the differential kinematics of any cross-section using screw theory. With the robot's parameterized shape and selected checkpoints on the obstacle's surface, we can determine the minimum distance between the robot and arbitrary obstacle, and locate the nearest point on the robot. Furthermore, we expand the null-space-based control method to accommodate redundant, non-redundant, and multiple continuum robots. An assessment of the avoidance capability is provided through an instantaneous and global criterion based on ellipsoids and possible movement ranges. Simulations and physical experiments involving continuum robots of different degrees of freedom performing various tasks were conducted to thoroughly validate the proposed framework. The results demonstrated its feasibility and effectiveness in minimizing the risk of collisions while maintaining the surgeon's control over the end effector. [ABSTRACT FROM AUTHOR]

Collision-free path planning is a crucial capability for industrial robot in its application. In this paper, a collision avoidance strategy based on virtual body deformation (VBDCAS) is proposed to improve the planning efficiency. The main idea of VBD-CAS is to realize the obstacle avoidance according to the allowable deformation space of the robotic arm relative to the obstacle. The obstacle avoidance evaluation model with spherical obstacle is established through the limit motion analysis of robotic arms. Then, a particle swarm optimization with VBDCAS (PSO-VBD-CAS) algorithm is developed for the collision-free path planning by integrating VBD-CAS into PSO algorithm. PSO-VBD-CAS algorithm uses obstacle avoidance evaluation model to judge weather the collision is happened between robotic arm and obstacles. When the joint angles of robot is located in the allowable deformation space of robotic arm, the robotic arm does not collide with obstacles. The proposed algorithm can directly perform the collision judgment without repeatedly performing forward kinematics solution of robot and shortest distance calculation from robotic arm to obstacles. Two simulations and an experiment are used to verify the validity of the proposed method. The validation results demostrate that the proposed VBD-CAS can effectively realize the collision detection, meanwhile the PSO-VBD-CAS algorithm has a better efficiency compared to distance-based obstacle avoidance path planning methods. [ABSTRACT FROM AUTHOR]

Herein, a control system and a fault tolerance method for the rotor positionable quadrotor are proposed. Quadrotors that have a variable structure are made for different purposes. The rotor‐positionable quadrotor studied here, is a type of drone with a variable structure that has the ability to change the position of its rotors linearly along the axis of each arm. It can be seen that this capability can improve the drone robustness against disturbances and faults in comparison with regular quadcopters. Due to the over‐actuated dynamics of this type of quadrotor, the control allocation scheme based on log‐barrier optimization is employed to obtain the position and speed of each rotor. In this study, it is experimentally shown that rotor positioning not only reduces power consumption but also increases roll and pitch control inputs magnitude. Furthermore, when a fault occurs as a decrease in rotor speed, a fuzzy method is proposed to position the rotors which tolerates the fault. Finally, numerical simulations and experimental tests verified that rotor positioning can bring more robustness, reduction in power consumption, and fault tolerance in some rotor faults capabilities for quadrotors. [ABSTRACT FROM AUTHOR]

Aiming at the disadvantages of traditional manual docking, such as low assembly efficiency and large positioning error, a six-DOF dual-arm robot system for module docking is designed. Firstly, according to the operation tasks of the cabin docking robot, its functional requirements and key indicators are determined, the overall scheme of the robot is designed, and the composition and working principle of the robot joints are introduced in detail. Secondly, a strength analysis of the core components of the docking robot is carried out by finite element analysis software to ensure its load capacity. Based on the kinematics model of the robot, the working space of the robot mechanism is simulated and analyzed. Finally, the experimental platform of the docking robot is built, and the working space, repeated positioning accuracy, and motion control accuracy of the docking robot mechanism are verified through experiments, which meet the design requirements. [ABSTRACT FROM AUTHOR]

In this article, the problems arising in the design of robots with parallel kinematics are defined. An analysis of the causes of these problems was made. Methods for solving the defined problems applied in modern robots with parallel kinematics are indicated. This article summarizes and presents all these problems and analyzes each of them, with the goal of serving as an initial guide for engineers in designing new cost-effective parallel robots that meet the needs of discrete manufacturing. There are many scientific works on this topic, but they are focused only on a specific problem, presenting a method for its solution. In most cases, these methods are not generalized and only apply to a specific type of construction. Therefore, when designing, engineers must study all these methods and carefully select the appropriate ones that give maximum performance, a process that is significantly time-consuming. That is why this article can help the design process by giving an initial view of all possible problems, and for some of them, specific solutions from different authors and companies are presented. Thus, the design time for engineers who have not encountered the features of parallel robots can be drastically reduced, something that is of great importance for today's automation. [ABSTRACT FROM AUTHOR]

An ARM Cortex simulation system for collaborative welding robots is presented in this paper. The components of the ARM Cortex SoC for embedded robot control, an OpenGL ES with image rendering, and a 3D geometry engine OpenCasCade for modeling are integrated for the purposes of simulating system self-controllability and cost effectiveness. This simulation of a collaborative welding robot achieved convenience while meeting the performance requirements; meanwhile, the auxiliary design was able to mark the trajectory of the robot's end effector and reveal the collaborative robot's inverse kinematic parameters, namely the position and Euler angle. An ARM Linux X11 Window environment that was set to create a 3D simulation rendering algorithm was built simultaneously. Then, the STEP model of the robot was loaded by using the OpenCasCade functionality. After that, the robot model and complex spline surface could be visualized by using the Qt QGLWidget. Finally, the correctness of the kinematic algorithm was verified by conducting simulations and analyzing the robot's kinematics through the simulation results, which could verify the expected design and provide a set of fundamental samples for the robot trajectory industry regarding welding applications. [ABSTRACT FROM AUTHOR]

This contribution focuses on solving the inverse and forward kinematics in the kinematic analysis of a two-link manipulator model. It involves determining the trajectory of the end effector through fifth-degree polynomial interpolation. Furthermore, given initial and final arm angle values, it computes not only the end effector trajectory but also the angular parameters of individual actuators in both arms. Additionally, it calculates the variations of angular parameters such as rotation angle, angular velocity, and angular acceleration in each kinematic pair. The direct kinematics task is utilized to define the manipulator's workspace. The task is carried out using Matlab software, and the results are presented in the form of graphs and tables. [ABSTRACT FROM AUTHOR]

In the pursuit of enhancing the efficiency of the inverse kinematics of SCARA robots with four degrees of freedom (4-DoF), this research delves into an approach centered on the application of Artificial Neural Networks (ANNs) to optimise and, hence, solve the inverse kinematics problem. While analytical methods hold considerable importance, tackling the inverse kinematics for manipulator robots, like the SCARA robots, can pose challenges due to their inherent complexity and computational intensity. The main goal of the present paper is to develop efficient ANN-based solutions of the inverse kinematics that minimise the Mean Squared Error (MSE) in the 4-DoF SCARA robot inverse kinematics. Employing three distinct training algorithms – Levenberg-Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG) – and three generated datasets, we fine-tune the ANN performance. Utilising diverse datasets featuring fixed step size, random step size, and sinusoidal trajectories allows for a comprehensive evaluation of the ANN adaptability to various operational scenarios during the training process. The utilisation of ANNs to optimise inverse kinematics offers notable advantages, such as heightened computational efficiency and precision, rendering them a compelling choice for real-time control and planning tasks. Through a comparative analysis of different training algorithms and datasets, our study yields valuable insights into the selection of the most effective training configurations for the optimisation of the inverse kinematics of the SCARA robot. Our research outcomes underscore the potential of ANNs as a viable means to enhance the efficiency of SCARA robot control systems, particularly when conventional analytical methods encounter limitations. [ABSTRACT FROM AUTHOR]