scholarly journals A study of the applications of a spring-assisted modular and reconfigurable robot for safe robot operation

2021 ◽  
Author(s):  
Harshita Patel
Keyword(s):  
Numerical Simulations ◽  
Trajectory Tracking ◽  
Brake System ◽  
Joint Position ◽  
Tracking Accuracy ◽  
Motor Shaft ◽  
Brake Rotor ◽  
Reconfigurable Robot ◽  
Safety Features ◽  
Capacity Performance

A novel spring-assisted modular and reconfigurable robot (SA-MRR) has been recently developed at our laboratory to reinforce its performance, and to enable safe and dexterous operations in human environments. A power spring is inserted between the brake rotor and the motor shaft through a decoupling bearing. With the spring engaged, the working range of the joint is mechanically limited for safe operations, and such a limited working range can be established at any joint position. The safety aspect of the SA-MRR is investigated by operating the robot in a limited workspace created by activating the spring. The trajectory tracking capability of the SA-MRR is explored by comparing trajectories followed by a conventional MRR and SA-MRR in a restricted workspace, while lifting a heavy payload. Trajectory tracking is performed with various payloads to demonstrate the SA-MRR’s superior payload handling capacity performance due to addition of the spring-generated moment. These algorithms have been implemented on a 3-DOF SA-MRR and numerical simulations have been carried out to investigate the improved tracking accuracy and safety features due to addition of the spring-brake system.

scholarly journals A study of the applications of a spring-assisted modular and reconfigurable robot for safe robot operation

2021 ◽  
Author(s):  
Harshita Patel
Keyword(s):  
Numerical Simulations ◽  
Trajectory Tracking ◽  
Brake System ◽  
Joint Position ◽  
Tracking Accuracy ◽  
Motor Shaft ◽  
Brake Rotor ◽  
Reconfigurable Robot ◽  
Safety Features ◽  
Capacity Performance

A novel spring-assisted modular and reconfigurable robot (SA-MRR) has been recently developed at our laboratory to reinforce its performance, and to enable safe and dexterous operations in human environments. A power spring is inserted between the brake rotor and the motor shaft through a decoupling bearing. With the spring engaged, the working range of the joint is mechanically limited for safe operations, and such a limited working range can be established at any joint position. The safety aspect of the SA-MRR is investigated by operating the robot in a limited workspace created by activating the spring. The trajectory tracking capability of the SA-MRR is explored by comparing trajectories followed by a conventional MRR and SA-MRR in a restricted workspace, while lifting a heavy payload. Trajectory tracking is performed with various payloads to demonstrate the SA-MRR’s superior payload handling capacity performance due to addition of the spring-generated moment. These algorithms have been implemented on a 3-DOF SA-MRR and numerical simulations have been carried out to investigate the improved tracking accuracy and safety features due to addition of the spring-brake system.

Modeling and trajectory tracking control of a two-wheeled mobile robot: Gibbs–Appell and prediction-based approaches

Robotica ◽  
2018 ◽  
Vol 36 (10) ◽  
pp. 1551-1570 ◽  
Author(s):  
Hossein Mirzaeinejad ◽  
Ali Mohammad Shafei
Keyword(s):  
Trajectory Tracking ◽  
Dynamic Models ◽  
Sliding Mode ◽  
Tracking Accuracy ◽  
Wheeled Mobile Robots ◽  
Tracking Errors ◽  
Trajectory Tracking Control ◽  
Control Laws ◽  
Control Approach ◽  
Prediction Time

SUMMARYThis study deals with the problem of trajectory tracking of wheeled mobile robots (WMR's) under non-holonomic constraints and in the presence of model uncertainties. To solve this problem, the kinematic and dynamic models of a WMR are first derived by applying the recursive Gibbs–Appell method. Then, new kinematics- and dynamics-based multivariable controllers are analytically developed by using the predictive control approach. The control laws are optimally derived by minimizing a pointwise quadratic cost function for the predicted tracking errors of the WMR. The main feature of the obtained closed-form control laws is that online optimization is not needed for their implementation. The prediction time, as a free parameter in the control laws, makes it possible to achieve a compromise between tracking accuracy and implementable control inputs. Finally, the performance of the proposed controller is compared with that of a sliding mode controller, reported in the literature, through simulations of some trajectory tracking maneuvers.

scholarly journals Q-learning trajectory planning based on Takagi–Sugeno fuzzy parallel distributed compensation structure of humanoid manipulator

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141983020 ◽  
Author(s):  
Shuhuan Wen ◽  
Xueheng Hu ◽  
Xiaohan Lv ◽  
Zongtao Wang ◽  
Yong Peng
Keyword(s):  
Reinforcement Learning ◽  
Trajectory Planning ◽  
Trajectory Tracking ◽  
Fuzzy Controller ◽  
Learning Algorithm ◽  
Fuzzy Model ◽  
Large Error ◽  
Learning Trajectory ◽  
Tracking Accuracy ◽  
Takagi Sugeno

NAO is the first robot created by SoftBank Robotics. Famous around the world, NAO is a tremendous programming tool and he has especially become a standard in education and research. Aiming at the large error and poor stability of the humanoid robot NAO manipulator during trajectory tracking, a novel framework based on fuzzy controller reinforcement learning trajectory planning strategy is proposed. Firstly, the Takagi–Sugeno fuzzy model based on the dynamic equation of the NAO right arm is established. Secondly, the design and the gain solution of the state feedback controller based on the parallel feedback compensation strategy are studied. Finally, the ideal trajectory of the motion is planned by reinforcement learning algorithm so that the end of the manipulator can track the desired trajectory and realize the valid obstacle avoidance. Simulation and experiment shows that the end of the manipulator based on this scheme has good controllability and stability and can meet the accuracy requirements of trajectory tracking accuracy, which verifies the effectiveness of the proposed framework.

scholarly journals Design of Augmented Nonlinear PD Controller of Delta/Par4-Like Robot

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Amjad J. Humaidi ◽  
Ahmed Ibraheem Abdulkareem
Keyword(s):  
Trajectory Tracking ◽  
Lyapunov Method ◽  
Dynamic Performance ◽  
Parallel Robot ◽  
Pd Controller ◽  
Comparison Study ◽  
Tracking Accuracy ◽  
Control Schemes ◽  
The Stability ◽  
Made In

This work presents the design of two control schemes for a Delta/Par4-like parallel robot: augmented PD (APD) controller and augmented nonlinear PD (ANPD) controller. The stability of parallel robot based on nonlinear PD controller has been analyzed and proved based on Lyapunov method. A comparison study between APD and ANPD controllers has been made in terms of performance and accuracy improvement of trajectory tracking. Also, another comparison study has been presented between augmented nonlinear PD (ANPD) controller and nonaugmented nonlinear PD (NANPD) controller in order to show the enhancement of introducing the augmented structure on dynamic performance and trajectory tracking accuracy. The effectiveness of augmented PD controllers (APD and ANPD) and nonaugmented nonlinear PD (NANPD) controller for the considered parallel robot are verified via simulation within the MATLAB environment.

Improvement of Trajectory Tracking Accuracy for Industrial Robot Arms by B-Spline

2004 ◽  
Vol 2004.57 (0) ◽  
pp. 387-388
Author(s):  
Makoto TAKATA ◽  
Hiroaki OZAKI ◽  
Makoto IWAMURA ◽  
Chang-jun LIN ◽  
Tetsuji SIMOGAWA
Keyword(s):  
Trajectory Tracking ◽  
Industrial Robot ◽  
Tracking Accuracy ◽  
B Spline ◽  
Robot Arms

scholarly journals Trajectory Tracking Method of Volleyball Player’s Arm Hitting Image Based on D-P Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hao Qin
Keyword(s):  
Trajectory Tracking ◽  
Three Dimensional ◽  
Feature Points ◽  
Tracking Accuracy ◽  
Tracking Method ◽  
Feature Extraction Method ◽  
Image Tracking ◽  
Volleyball Players ◽  
Long Time ◽  
Tracking Time

Aiming at the problems of poor image tracking effect, low precision, and long time in the process of image tracking of volleyball player’s arm hitting, a volleyball player's arm hitting image tracking method based on D-P algorithm is proposed. This paper analyzes the basic concept, basic principle, and basic equation of D-P algorithm and collects the arm stroke trajectory image of volleyball players under the three-dimensional visual model. Using wavelet multiscale decomposition method, the arm stroke trajectory of volleyball players is filtered, and the edge contour feature points of the arm stroke image of volleyball players are extracted. Using the gray histogram feature extraction method, the gray information of volleyball player's arm hitting trajectory image is enhanced. Combined with pixel adaptive enhancement technology, the key action feature points of volleyball player's arm hitting image trajectory are located. Based on D-P algorithm, the volleyball player's arm hitting image trajectory is adjusted and modified to realize the correct tracking of volleyball player's arm hitting image trajectory. The experimental results show that the trajectory tracking effect of volleyball player's arm hitting image is better, which can effectively improve the tracking accuracy and shorten the tracking time.

Linear-extended-state-observer-based prescribed performance control for trajectory tracking of a robotic manipulator

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bingjie Xu ◽  
Shuai Ji ◽  
Chengrui Zhang ◽  
Chao Chen ◽  
Hepeng Ni ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Tracking Error ◽  
Robotic Manipulator ◽  
Tracking Accuracy ◽  
Content Type ◽  
Prescribed Performance ◽  
Active Disturbance Rejection ◽  
Prescribed Performance Control ◽  
Disturbance Rejection Control ◽  
Linear Extended State Observer

Purpose Trajectory tracking error of robotic manipulator has limited its applications in trajectory tracking control systems. This paper aims to improve the trajectory tracking accuracy of robotic manipulator, so a linear-extended-state-observer (LESO)-based prescribed performance controller is proposed. Design/methodology/approach A prescribed performance function with the convergence rate, maximum overshoot and steady-state error is derived for the output error transformation, whose stability can guarantee trajectory tracking accuracy of the original robotic system. A LESO is designed to estimate and eliminate the total disturbance, which neither requires a detailed system model nor a heavy computation load. The stability of the system is proved via the Lyapunov theory. Findings Comparative experimental results show that the proposed controller can achieve better trajectory tracking accuracy than proportional-integral-differential control and linear active disturbance rejection control. Originality/value In the LESO-based prescribed performance control (PPC), the LESO was incorporated into the PPC design, it solved the problem of stabilizing the complex transformed system and avoided the costly offline identification of dynamic model and estimated and eliminated the total disturbance in real-time with light computational burden. LESO-based PPC further improved control accuracy on the basis of linear-active-disturbance-rejection-control. The new proposed method can reduce the trajectory tracking error of the robotic manipulators effectively on the basis of simplicity and stability.

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