(FFNN) is used to compensate for the robot dynamics. The FFNN computes the required torques to drive the robot manipulator to achieve desired tracking. The stability of combined PI kinematic and FFNN computed torque is proved by Lyapunov theory. Simulation results are carried out for 3 DOF articulated robot manipulator to evaluate the controller performance.

In this paper, a dynamic analysis for 5 degree of freedom (DOF) robotic arm with serial topology is presented. The model the robot based on importing tri-dimensional CAD into Simulink®-Simscape™-Multibody™. in Simscape necessary and important step development mechanical structure robot. correct choice electric motors made according to resistant joint torques determined by running analysis. One ...

Abstract Variable Stiffness Actuator (VSA) is the core mechanism to achieve physical human–robot interaction, which an inevitable development trend in robotic. The existing variable stiffness actuators are basically single degree-of-freedom (DOF) rotating joints, achieving multi-DOF motion by cascades and resulting complex robot body structures. In this paper, integrated 2-DOF actuator with pro...

The Korea Advanced Institute of Science and Technology (KAIST) humanoid robot 1 (KHR-1) was developed for the purpose of researching the walking action of bipeds. KHR-1, which has no hands or head, has 21 degrees of freedom (DOF): 12 DOF in the legs, 1 DOF in the torso, and 8 DOF in the arms. The second version of this humanoid robot, KHR-2, (which has 41 DOF) can walk on a living-room floor; i...

This paper presents a discrete-time decentralized control scheme for trajectory tracking of a two degrees of freedom (DOF) robot manipulator. A modified recurrent high order neural network (RHONN) structure is used to identify the plant model and based on this model, a discrete-time control law is derived, which combines block control and sliding mode techniques. The neural network learning is ...

This paper reviews the literature on control of 2-DOF robot manipulator using fuzzy logic control (FLC). Different schemes of FLC laws are considered here. These are PID control, sliding mode control (SMC), and adaptive control. Importance of each control techniques with its advantages and disadvantages is discussed here. It is highlighted that the robustness of the system has improved consider...

We propose a novel framework for Deep Reinforcement Learning (DRL) in modular robotics using traditional robotic tools that extend state-of-the-art DRL implementations and provide an end-to-end approach which trains a robot directly from joint states. Moreover, we present a novel technique to transfer these DLR methods into the real robot, aiming to close the simulation-reality gap. We demonstr...

This paper presents a discrete-time decentralized control scheme for trajectory tracking of a two degrees of freedom (DOF) robot manipulator. A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The neural network learning is performed on-line by Kalman filtering. The contr...

OBJECTIVE We present an algorithm that enables percutaneous needle-placement procedures to be performed with unencoded, unregistered, minimally calibrated robots while removing the constraint of placing the needle tip on a mechanically enforced Remote Center of Motion (RCM). MATERIALS AND METHODS The algorithm requires only online tracking of the surgical tool and a five-degree-of-freedom (5-...