Simulation and Analysis of an Adaptive Manipulator Based on Machine Learning

In the control of flexible manipulators, most work in the literature concentrates on the suppression of link deformations. In this study, the aim is not to suppress the deflections, but to calculate joint angles to minimize the tip position error. A gradient descent method is utilized off-line for the trajectory planning of a two-link flexible manipulator under gravity. Fuzzy logic control with gravity compensation is applied for the position control of the manipulator where the reference inputs are the values of the joint angles as determined by the trajectory planning procedure. Simulations have been carried out to show the performance of both the trajectory planning method and of the fuzzy controller in a regulation problem. Results are illustrated both in the joint space and in the operational space.

Jumping is a fundamental capability for wheeled-bipedal robots (WBRs) navigating unstructured terrains, with jump height and stability serving as indicators of the robot's environmental adaptability. However, existing trajectory planning methods demand high output capacity from the joints and fail to balance computational load with trajectory tracking performance. This limitation hinders most robots from experimental validation. To address these challenges, this study presents an optimized virtual model, trajectory planning strategy, and control method. These solutions enhance both the height and stability of jumps while ensuring real-time execution on physical robots. Firstly, inspired by the human jumping mechanism, a Nonlinear Wheel-Spring-Loaded Inverted Pendulum (NW-SLIP) model was originally proposed as the virtual model for trajectory planning. The jump height is increased by 3.4 times compared to the linear spring model. Then, cost functions are established based on this virtual model, and the trajectory for each stage is iteratively optimized using Quadratic Programming (QP) and a bisection method. This leads to a 21.5% increase in the maximum jump height while reducing the peak joint torque by 14% at the same height. This significantly eases execution and enhances the robot's trajectory-tracking ability. Subsequently, a leg statics model is introduced alongside the kinematics model to map the relationship between the virtual model and joint space. This approach improves trajectory tracking performance while circumventing the intricate calculation of the dynamics model, thereby enhancing jump consistency and stability. Finally, the proposed trajectory planning and jump control method is validated through both simulations and real-world experiments, demonstrating its feasibility and effectiveness in practical robotic applications.

This paper analyses the working mechanism of hydraulic robotic excavator. By using Denavit-Hartenberg matrix, the kinematics model of working mechanism is established. The transform relationships among the configuration space, joint space and drive space are deduced as well. In addition, a trajectory planning method is presented to improve the movement stability of hydraulic robotic excavator. Compared with other methods, this method takes the velocity and acceleration factors of each hydraulic cylinder into account, which makes the trajectory more stable. In addition, time intervals are considered as the the design variables, which not only can guarantee the accuracy of the original trajectory, but also have fewer variables. Under the restrictions of kinematics, trajectory planning of the excavator is completed. With genetic algorithm, the proposed method is verified through simulation. The results show that the presented method can decrease the fluctuation of velocity and the saltation of acceleration efficiently in trajectory planning.

Modelling cylindrical manipulator with three degrees of freedom for pick and place operation considered forward kinematics using Denavit-Hartenberg (DH). Transformation of manipulator from one position to the other mathematicallydone using DH. The output of theoretical results such as joint angles and link length is considered as input for robotic toolbox in MATLAB. Pneumatic manipulator is built-in automation studio software andverified the simulation. Threepneumatics cylinders are considered for the development of three degrees of freedom manipulator connected in sequence for each operation. The main concept of this paper is to build a pick and place pneumatic manipulator using Automation studio (AS)and simulate. Thepick and place pneumatic manipulator aredeveloped and controlled by Programmable logic control (PLC) ladder logic in AS.

The advancement of the Intelligent Transport Systems (ITS) and the emerging Connected and Automated Vehicles (CAVs) technology are acknowledged to hold a great potential to mitigate challenging problems in the current transportation networks. Particularly, a proper traffic control strategy with a precise vehicular movement control scheme can alleviate the congestion and improve the safety and efficiency of the traffic. This paper proposes a novel bi-level control framework that combines a design of traffic signal timings at a network level, and a detailed trajectory control policy for individual vehicles at a link-level within a network of CAVs. We develop a group-based longitudinal trajectory planning scheme to coordinate vehicular movements at the lower level of our framework while abiding by the signal operations along with end-to-end vehicle routing decisions from the upper network level optimization. This joint and mutual interaction between the two different control strategies in the urban signalized corridors is complex and can significantly affect the overall network's performance, nevertheless has not been explored previously in the literature. The proposed framework enables such studies where we derive an efficient algorithm that iteratively solves the mixed-integer linear programming (MILP) and linear programming models in each link at the lower and over the network at the upper levels, respectively. Numerical results show the effectiveness of the proposed joint control framework in network performance regarding the average travel time, queue formation and dissipation across the network.

With the continuous development of industrial automation, robots are applied to various fields of industry increasingly, and the robot pose accuracy become an important issues. Through the establishment of the robot parameterized virtual prototype model, the error of bar length, joint angle and joint space have been taken into account, and the Monte Carlo sampling method is used to process a number of simulation analysis. The reliable probability which is given within the error limits is calculated, and finally through sensitivity analysis, the conclusion is drawn that different error factors influent the robot end error differently, which have a certain significance for the allocation of the manufacturing tolerances of the robot and trajectory planning.

Robotic arms are widely used in industrial automation due to their simple structure, high flexibility, and moderate cost, especially in standardized scenarios such as conveyor belt operations. This study focuses on a three-axis robotic arm, addressing the demands of conveyor belt operations through modeling and performance analysis. First, precise structural modeling of the robotic arm was completed using SolidWorks, and its kinematic model was established using the D-H parameter method. Second, trajectory planning of the end-effector was studied based on task-specific requirements, and the variations in joint angles, velocities, and accelerations were analyzed through simulations. Finally, the smoothness of paths and workspace coverage were evaluated via simulations. Results indicate that the three-axis robotic arm can meet the demands of conveyor belt operations with good applicability. However, further improvements in control precision and dynamic stability are needed for more complex, non-standardized scenarios. This study provides theoretical support for the design optimization and broader application of three-axis robotic arms.

This paper proposes a strategy to predict the accurate shuttlecock trajectory and motion planning of the badminton robot using Kalman filter and Proportional-Integral-Derivative (PID) control. A PID control is used to accurately control and hold the position of the robot in a standard indoor badminton court. The conventional Kalman Filter and its various versions are mostly used to acquire the current state of the system, but the proposed modified Kalman Filter in this paper is used to predict the accurate trajectory of the shuttlecock. The effectiveness of the proposed strategy is validated experimentally for different trajectories and motion planning.

In this paper, a trajectory planning and a control for biped robots with toe and heel joints are shown. We added toe and heel joints to a basic biped robot. A trajectory planning is extended for the walking with the toe and heel joints. Using this mechanism and this trajectory planning, the stride can be increased more. Additionally, a control planning is presented for division of walking stabilization and environmental adaptation. A time-based switching impedance controller with the toe and heel joints is proposed for adaptation to uneven terrain. Using this control planning and the proposed method, the stable walking on the rough terrain is realized. The validity is confirmed by experimental results.

This paper presents a biological inverse kinematics (IK) method and a trajectory tracking approach for a 7-DOF robotic manipulator. The system structure of the manipulator is first designed and its forward kinematics is then derived using its Denavit-Hartenberg (DH) parameters. Based on the DH model, an inverse kinematics method using the combination of particle-swarm optimization (PSO) and real coded genetic algorithm (RGA) is proposed to find the seven joint angles of the manipulator while moving from one point to another, and then a smooth continuous trajectory is planned by connecting several via points. For trajectory tracking, a Jacobian inverse kinematic method along with a P controller and PI speed joint controllers is used to achieve trajectory tracking control with an acceptable accuracy. The effectiveness and merit of the proposed trajectory planning and tracking methods are well exemplified by conducting two simulations.

Purpose This study aims to propose a method for collision avoidance and hovering, enabling robots to perform efficient and safe inspection tasks in complex inlet environments, while also having capabilities for collision avoidance and trajectory planning. Through precise trajectory planning, the robot can safely enter and exit the inlet environment, ensuring the safety and efficiency of the inspection process. Design/methodology/approach A novel robot configuration was proposed, and by integrating the genetic algorithm-particle swarm optimization (GA-PSO) algorithm and sensor fusion technology, a collision-avoidance and immersion trajectory planning method was designed. The feasibility of the proposed method was verified through computer simulation and experiments. Findings Through experimental verification, the air intake duct inspection robot achieved remarkable performance in the simulated air intake duct experimental environment. The robot was able to successfully complete complex inspection tasks. Originality/value The innovation of this research lies in combining machine learning with robot navigation technology and innovatively applying the GA-PSO algorithm to optimize robot trajectory planning in a complex intake environment to solve the intake inspection problem in practical applications. By autonomously optimizing the joint angles, an efficient automated inspection process is achieved, reducing the risk and cost of manual inspection. It not only optimizes the motion path of the robot, but also enhances its adaptability and stability in complex environments, providing a more efficient and reliable solution for air intake inspection.

This book is the second edition of a textbook published in 1996 by McGraw Hill and originates from a graduate level course given by the authors at the University of Naples. The topics include kinematics, statics and dynamics of robot manipulators together with trajectory planning and active control. There are only minor additions the first edition, which are mainly the use of quaternion to describe the orientation of the end effector and a short description of a closed chain architecture for a manipulator (parallelogram arm). The book is largely devoted to serial manipulators, with special developments about active control including adaptative control, robust controls and stability analysis. Another strength of this book is the great number of problems proposed at the end of each chapter, together with a list of references related to it. The fundamental features covered by the text are illustrated on simple examples of serial manipulators (two-link planar arm, parallelogram arm) including analytical results and numerical tests.The book has nine chapters followed by three appendices. The first appendix is devoted to linear algebra, the second recalls some fundamental aspects of rigid body mechanics and the third gives some basic principles of feedback control of linear systems.Chapter one is an introduction to the study of robot manipulators, giving an interesting classification of their architectures, the corresponding workspace and describes the tasks for which theyare used. After some standard examples of industrial manipulators, bibliographical reference texts are proposed, including textbooks on modelling and control of robots, general books on robotics, specialized texts, scientific robotic reviews and some international conferences on robotics.Chapters two, three and four are devoted to mechanical modelling of robot manipulators. The fundamental basics of kinematics are given in chapter two, including the representation of finite rotations by Euler angles or unit quaternions, homogeneous transformations, Denavit-Hartenberg parameters and workspace. The direct and inverse kinematical problems are solved in analytical form for some typical manipulator structures. The differential kinematics of robots are presented in chapter three, with an introduction to the geometric and analytic Jacobian matrices, kinematic singularities and redundancy. The inverse kinematic problem is presented, with special attention to the case of redundant robots where the solution is obtained by a linear optimization problem leading to the introduction of the pseudo-inverse Jacobian matrix and to the solution of several objectives such as avoidance of collision with an obstacle or moving away from singularities. Several inverse kinematics algorithms are given wih an interesting application to a three-link planar arm. Finally, a property of kineto-statics duality is deduced from the principle of virtual work applied to an equilibrium configuration of the robot. Chapter four is a standard presentation of the derivation of the dynamical model by Lagrange formulation and then by the Newton-Euler method. In the Lagrange formulation method, the linearity with respect to inertial parameters is shown and a detailed formulation of the dynamical model is obtained for a two-link Cartesian arm, a two-link planar arm and a parallelogram arm. The problem of dynamic parameter identification is also briefly presented from a numerical point of view. The recursive algorithm constructed from the Newton-Euler formulation is presented and illustrated by considering a two-link planar arm. Finally, the operational space dynamic model is introduced.In chapter five, paths and trajectory planning in joints and in operational spaces are presented; several classical methods of interpolation are described.Chapter six is an extensive study of active control of manipulators. Several methods are presented, involving classical independent joint control, non-linear centralized control, robust control and adaptative control. Both joint-space control and operational-space control are studied together with stability analysis by using Liapounoff functions. An interesting application to the two-link planar arm already used shows the comparison between various control schemes.Chapter seven deals with interaction control of serial manipulators with the working environment. Several strategies involving compliance control, impedance control, force control and hybrid control are presented.Chapter eight describes the actuators and the sensors used in robotics. Several types of servomotors (electric and hydraulic) are presented, together with the model giving their input/output relationship. Several kinds of sensors are also described including encoders, tachometers, force and vision sensors.The last chapter gives a short presentation of the functional architecture of a robot's control system, including characteristics of the programing environment and the hardware architecture.In conclusion, the book provides a good insight about simulation and control of robot manipulators, with a detailed study of the various control strategies and several interesting and pedagogical applications. This book is an excellent review of the standard knowledge needed not only for graduate students but also for researchers interested in robot manipulators.M Pascal

Kinematic modeling is essential for planning and controlling continuum robot motion. The traditional Denavit Hartenberg (DH) model involves complex matrix multiplication operations, resulting in computationally intensive inverse solutions and trajectory planning. Solving position and orientation changes in continuum robots using the double quaternion rule can reduce computational complexity. However, existing dual quaternion methods are direct equational transformations of DH rules and do not give a complete modeling process. They usually require more interpretability when applying continuum robot kinematic modeling. This paper uses the dual quaternion method to establish a kinematic model of a continuum robot. It uses a two-section continuum robot model to compare the advantages of dual quaternion and traditional modeling methods. In addition, this paper proposes a five-polynomial interpolation algorithm based on the dual quaternion method for trajectory planning of continuum robots. This method accurately models spatial bending and torsional motions of singularity-free continuum robots.

This paper studies the Cartesian point-to-point optimal trajectory planning for space robots oriented to space maintenance operations. Aiming at the problems of poor stability, large base disturbance, and large joint variation in the motion planning of point-to-point maintenance in space, a planning method is proposed to minimize the base disturbance and the total joint angle variation under the jerk constraint on the premise of ensuring the accuracy of the end pose. First, the attitude of the space robot is described by the unit quaternion, and the velocity relationship between the joint angle, the end effector, and the base posture is introduced. Then, the joint trajectories were parameterized by a fifth degree polynomial, and a trajectory planning model with the minimum perturbation of the base and the minimum variation of the joint of the manipulator was established under the condition that the end effector satisfied the pose and the jerk constraint. Finally, a multi-objective optimization algorithm is proposed to deal with the trajectory optimization problem under nonlinear constraints. The simulation results show that the proposed trajectory planning method can optimize the base attitude and joint angle of the space manipulator under the premise of the optimal trajectory and stability of the terminal execution tool, which ensures the stability of the space robot's on-orbit service and reduces the energy consumption.

Robots are used to provide help in unsafe, repetitive and dreary situations. This paper concentrates on a robotic arm which can be utilized for crossing of the dead wire structure to the jumper cable of an electrical transmission line. In order to achieve a good positional accuracy of the end-effector, the robotic arm is modeled and analyzed. Denavit-Hartenberg (DH) representation is used for the kinematic modeling and Lagrangian-Euler (LE) method for the dynamic modeling. Since the kinematic and dynamic modeling of robotic arm is highly nonlinear in nature, the optimum trajectory planning is a challenging issue in almost all obstacle avoidance problems. In trajectory planning, the desired trajectory needs to be followed for end-effector positioning. This paper presents kinematic modeling, dynamic modeling, workspace analysis and trajectory planning of a 5 Degree of freedom (DOF) robotic arm. The robotic arm is designed using SolidWorks 2014 software. The complete analysis of the proposed manipulator is simulated using MATLAB Software.