Research on Kinematics Analysis and Trajectory Planning of Novel EOD Manipulator

2021 ◽  
Vol 11 (20) ◽  
pp. 9438
Author(s):  
Jianwei Zhao ◽  
Tao Han ◽  
Xiaofei Ma ◽  
Wen Ma ◽  
Chengxiang Liu ◽  
...  
Keyword(s):  
Trajectory Planning ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Random Number ◽  
Polynomial Interpolation ◽  
Interpolation Method ◽  
Joint Space ◽  
Work Requirements ◽  
Multiple Degrees Of Freedom ◽  
Quintic Polynomial

To address the problems of mismatch, poor flexibility and low accuracy of ordinary manipulators in the complex special deflagration work process, this paper proposes a new five-degree-of-freedom (5-DOF) folding deflagration manipulator. Firstly, the overall structure of the explosion-expulsion manipulator is introduced. The redundant degrees of freedom are formed by the parallel joint axes of the shoulder joint, elbow joint and wrist pitching joint, which increase the flexibility of the mechanism. Aiming at a complex system with multiple degrees of freedom and strong coupling of the manipulator, the virtual joint is introduced, the corresponding forward kinematics model is established by D–H method, and the inverse kinematics solution of the manipulator is derived by analytical method. In the MATLAB platform, the workspace of the manipulator is analyzed by Monte Carlo pseudo-random number method. The quintic polynomial interpolation method is used to simulate the deflagration task in joint space. Finally, the actual prototype experiment is carried out using the data obtained by simulation. The trajectory planning using the quintic polynomial interpolation method can ensure the smooth movement of the manipulator and high accuracy of operation. Furthermore, the trajectory is basically consistent with the simulation trajectory, which can realize the work requirements of putting the object into the explosion-proof tank. The new 5-DOF folding deflagration manipulator designed in this paper has stable motion and strong robustness, which can be used for deflagration during the COVID-19 epidemic.

The Kinematic Analysis and Trajectory Planning Study of High-Speed SCARA Robot Handling Operation

2014 ◽  
Vol 687-691 ◽  
pp. 294-299 ◽  
Author(s):  
Guo Qing Ma ◽  
Zheng Lin Yu ◽  
Guo Hua Cao ◽  
Yan Bin Zheng ◽  
Li Liu
Keyword(s):  
Trajectory Planning ◽  
Inverse Kinematics ◽  
High Speed ◽  
Polynomial Interpolation ◽  
Interpolation Method ◽  
Joint Space ◽  
Parameter Design ◽  
Matlab Simulation ◽  
Scara Robot ◽  
Cubic Polynomial

Successfully developed of high-speed SCARA robot provides the possibility for fast handling. After analyzed the mechanical structure of SCARA robot, the kinematics equations were built to analyze forward and inverse kinematics problems based on modified D-H coordinate system theory. The trajectory planning was achieved by using the cubic polynomial interpolation method in joint space over the path points combined with motion parameters, the kinematics and trajectory planning were simulated by using matlab simulation platform. Simulation results show that robot parameter design is reasonable and the trajectory planning by interpolation calculation in joint space is feasible.

Take-Off Motion Planning of Legged Hopping Robot with Redundancy Characteristic

2013 ◽  
Vol 823 ◽  
pp. 127-130
Author(s):  
Yong Bo Li ◽  
Min Qiang Xu ◽  
Yu Wei
Keyword(s):  
Boundary Condition ◽  
Motion Planning ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Polynomial Interpolation ◽  
Hopping Robot ◽  
Continuous Scale ◽  
Quartic Polynomial ◽  
Driving Torque ◽  
Joint Limit

The planning for four-joint legged hopping robot with two redundant degrees of freedom at the take-off stage is researched. According to the take-off velocity and the boundary condition of centroid motion, the trajectory is planned with variable quartic polynomial interpolation. From inverse kinematics, the motion planning with redundancy characteristic is completed by using the GPM with continuous scale factor. Performance index of avoiding joint limit and optimizing joint driving torque are realized. The data indicates the feasibility and practicability of this algorithm.

Control of a Handwriting Robot with DOF Redundancy Based on Feedback in Task Coordinates

2004 ◽  
Vol 16 (4) ◽  
pp. 381-387 ◽  
Author(s):  
Hiroe Hashiguchi ◽  
◽  
Suguru Arimoto ◽  
Ryuta Ozawa
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Sensory Feedback ◽  
Closed Loop ◽  
Joint Space ◽  
Hand Dexterity ◽  
Loop Dynamics ◽  
Additional Input ◽  
Ill Posed ◽  
Joint Motions

To enhance robot hand dexterity, it is said that the robot should be designed to have a redundant number of degrees of freedom. In redundant robotic systems, inverse kinematics from task description space to joint space becomes ill-posed, making it difficult to determine joint motions. To avoid this ill-posedness, most proposed methods introduce an additional input term calculated from an intentionally introduced artificial index of performance. We propose a 4 DOF redundant handwriting robot using novel simple control to solve the problem of ill-posedness based on sensory feedback. We demonstrate the effectiveness of proposed control in computer simulation of closed-loop dynamics with the constraint that the robot’s endpoint be always on a two-dimensional plane.

Optimal Continuous Path Planning for Seven-Degrees-of-Freedom Robots

1986 ◽  
Vol 108 (3) ◽  
pp. 213-218 ◽  
Author(s):  
B. Benhabib ◽  
A. A. Goldenberg ◽  
R. G. Fenton
Keyword(s):  
Path Planning ◽  
Trajectory Planning ◽  
Degrees Of Freedom ◽  
Polynomial Interpolation ◽  
Continuous Path ◽  
End Effector ◽  
Joint Level ◽  
Redundant Robots ◽  
Planning And Control ◽  
Optimization Search

The paper addresses the problem of end effector trajectory planning and control of seven degrees of freedom (DOF) kinematically redundant robots. An off-line optimal continuous path planning method is developed for on-line control at joint level. The specified end effector path is approximated by a set of location nodes selected on the desired path. The motion control of the robot is provided by cubic polynomial interpolation at joint level. The proposed approach to trajectory planning of kinematically redundant robots consists of obtaining an optimal set of nodes which guarantees minimum deviation from the desired Cartesian path. The redundant DOF of the robot is used as a constrained variable in the optimization search. The method is illustrated in an example.

scholarly journals Design and Implementation of a Graphic Simulator for Calculating the Inverse Kinematics of a Redundant Planar Manipulator Robot

2020 ◽  
Vol 10 (19) ◽  
pp. 6770
Author(s):  
Claudio Urrea ◽  
Daniel Saa
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Interpolation Method ◽  
Probabilistic Method ◽  
Computational Simulations ◽  
Third Order ◽  
End Effector ◽  
Graphic Interface ◽  
Order Polynomial ◽  
Manipulator Robot

In this paper, a graphics simulator that allows for characterizing the kinematic and dynamic behavior of redundant planar manipulator robots is presented. This graphics simulator is implemented using the Solidworks software and the SimMechanics Toolbox of MATLAB/Simulink. To calculate the inverse kinematics of this type of robot, an algorithm based on the probabilistic method called Simulated Annealing is proposed. By means of this method, it is possible to obtain, among many possibilities, the best solution for inverse kinematics. Without losing generality, the performance of metaheuristic algorithm is tested in a 6-DoF (Degrees of Freedom) virtual robot. The Cartesian coordinates (x,y) of the end effector of the robot under study can be accessed through a graphic interface, thereby automatically calculating its inverse kinematics, and yielding the solution set with the position adopted by each joint for each coordinate entered. Dynamic equations are obtained from the Lagrange–Euler formulation. To generate the joint trajectories, an interpolation method with a third order polynomial is used. The effectiveness of the developed methodologies is verified through computational simulations of a virtual robot.

Analytical Trajectory Optimization of Seven Degrees of Freedom Redundant Robots

1987 ◽  
Vol 11 (4) ◽  
pp. 197-200 ◽  
Author(s):  
B. Benhabib ◽  
R.G. Fenton ◽  
A.A. Goldenberg
Keyword(s):  
Trajectory Planning ◽  
Trajectory Optimization ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Optimization Procedure ◽  
Redundant Robots ◽  
Point Motion ◽  
Point To Point ◽  
Lagrange’S Method

The basic characteristic of kinematically redundant robots is that non-unique joint solutions may exist for a specified end effector location. Thus, trajectory planning for a kinematically redundant robot requires an optimization procedure to determine the joint displacements when solving the inverse kinematics relations. In this paper an analytical solution is developed for the trajectory optimization problem of redundant robots based on the classical Lagrange’s method. A detailed formulation is provided for seven degrees of freedom robots, which minimizes the Euclidean norm of joint dislacements for point-to-point motion trajectory planning.

Natural Resolution of Ill-Posed Inverse Kinematics for Redundant Robots: A Challenge to Bernstein’s Degrees-of-Freedom Problem

2006 ◽  
Vol 18 (5) ◽  
pp. 651-660 ◽  
Author(s):  
Suguru Arimoto ◽  
◽  
Masahiro Sekimoto ◽  
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Sensory Feedback ◽  
Joint Space ◽  
Dimensional Manifold ◽  
Reaching Task ◽  
Loop Dynamics ◽  
Ill Posed ◽  
Human Limb ◽  
Joint Velocity

Over half a century ago, A. N. Bernstein observed that “dexterity” in human limb movement emerges from the involvement of multijoint motion with surplus degrees of freedom (DOF). Robotics posits that DOF redundancy in robot may enhance dexterity and versatility. Kinematic redundancy involves the problem of ill-posed inverse kinematics from task-description space to joint space. This problem is conventionally avoided by introducing an artificial performance index and uniquely determining an inverse kinematics solution by minimizing it. Instead of taking this conventional avoidance solution, we propose challenging Bernstein’s DOF problem by introducing two direct novel concepts - stability on a manifold and transferability to a submanifold - in dealing with human multijoint movement in reaching and showing that sensory feedback from task space to joint space together with adequate damping (joint velocity feedback) enables any solution to overall closed-loop dynamics to converge naturally and coordinately to a lower-dimensional manifold describing a set of joint states fulfilling a given motion task. This means that a reaching task is accomplished by sensory feedback with the appropriate choice of a stiffness parameter and damping coefficients without having to consider inverse kinematics. We also show that these concepts cope with the annoying “variability” of redundant joint motion seen typically in skilled human reaching. In conclusion, we propose a virtual spring/damper hypothesis that leads to natural control of skilled movement in redundant multijoint reaching.

Humanoid Robot Arm Kinematics Modeling and Motion Planning

2014 ◽  
Vol 644-650 ◽  
pp. 247-250
Author(s):  
Qin Jun Du ◽  
Xue Yi Zhang ◽  
Shi Long Zhai
Keyword(s):  
Trajectory Planning ◽  
Humanoid Robot ◽  
Joint Angle ◽  
Interpolation Method ◽  
Angular Acceleration ◽  
Polynomial Method ◽  
Robot Arm ◽  
Quintic Polynomial ◽  
Kinematics Modeling ◽  
Cubic Polynomial

This paper establishes the kinematics model of humanoid robot arm, the arm forward kinematics equations were built and solved, based on the advantages of CCD (Cyclic Coordinate Descent) and BFS (Broyden-Fletcher-Shanno) algorithm to solve the inverse kinematics of humanoid robot arm. In the joint space, using cubic polynomial and quintic polynomial interpolation method respectively for each joint angle interpolation. Cubic polynomial trajectory planning can meet the point-to-point movement in general, but can not guarantee the continuity of acceleration of each point; Quintic polynomial trajectory planning can ensure that each point is continuous of the joint angle, angular velocity, and angular acceleration, so this polynomial method can meet the movement of the humanoid robot arm.

scholarly journals Trajectory Planning of Robot Manipulator Based on RBF Neural Network

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1207
Author(s):  
Qisong Song ◽  
Shaobo Li ◽  
Qiang Bai ◽  
Jing Yang ◽  
Ansi Zhang ◽  
...  
Keyword(s):  
Neural Network ◽  
Trajectory Planning ◽  
Polynomial Interpolation ◽  
Robot Manipulator ◽  
Rbf Neural Network ◽  
Tracking Error ◽  
Lyapunov Theory ◽  
Degree Of Freedom ◽  
Quintic Polynomial ◽  
High Degree

Robot manipulator trajectory planning is one of the core robot technologies, and the design of controllers can improve the trajectory accuracy of manipulators. However, most of the controllers designed at this stage have not been able to effectively solve the nonlinearity and uncertainty problems of the high degree of freedom manipulators. In order to overcome these problems and improve the trajectory performance of the high degree of freedom manipulators, a manipulator trajectory planning method based on a radial basis function (RBF) neural network is proposed in this work. Firstly, a 6-DOF robot experimental platform was designed and built. Secondly, the overall manipulator trajectory planning framework was designed, which included manipulator kinematics and dynamics and a quintic polynomial interpolation algorithm. Then, an adaptive robust controller based on an RBF neural network was designed to deal with the nonlinearity and uncertainty problems, and Lyapunov theory was used to ensure the stability of the manipulator control system and the convergence of the tracking error. Finally, to test the method, a simulation and experiment were carried out. The simulation results showed that the proposed method improved the response and tracking performance to a certain extent, reduced the adjustment time and chattering, and ensured the smooth operation of the manipulator in the course of trajectory planning. The experimental results verified the effectiveness and feasibility of the method proposed in this paper.

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