Articulated robot

About: Articulated robot is a research topic. Over the lifetime, 4364 publications have been published within this topic receiving 52442 citations.

The Control of an Elastic Manipulation Device using DSP

Abstract: In fast robots with conventional control, the elasticities of gears and robot arms frequently result in disturbing vibrations around the desired tracks. These vibrations can only be counteracted by means of a precise system description and a tailored control concept. Starting with a specially constructed three-joint elastic articulated robot, computer support is used to * set up the nonlinear equations of motion, * identify the system parameters, * optimize a controller structure designed for the overall system and to * implement the controller with fast DSP hardware. Experimental tests with the designed control show considerable improvements on conventional approaches when fast tracking is considered.

A Hybrid Intelligent Active Force Controller for Articulated Robot Arms Using Dynamic Structure Neural Network

Abstract: The key feature of this paper is the application of a robotic control concept – Active Force Control (AFC) In this type of control, the unknown friction effect of the robotic arm may be compensated by the AFC method AFC involves the direct measurement of the acceleration and force quantities and therefore, the process of estimating the system ‘disturbance’ due to friction becomes instantaneous and purely algebraic However, the AFC strategy is very practical provided a good estimation of the inertia matrix of articulated robot arm is acquired A dynamic structure neural network – Growing Multi-experts Network (GMN) is developed to estimate the robot inertia matrix The growing and pruning mechanism of GMN ensures the optimum size of the network that results in an excellent generalization capability of the network Active Force Control (AFC) in conjunction with GMN successfully reduces the velocity and position tracking errors in spite of robot joint friction The embedded GMN is capable of coupling the inertia matrix estimation on-line that clearly enhances the performance of AFC controller The robustness and effectiveness of the new hybrid neural network-based AFC scheme are demonstrated clearly with regard to two link articulated robot and a simulated two-degree of freedom Puma 560 robot

Multiple robot coordination and programming

Abstract: The complexity of multiple robot coordination has added more functions to robot programming. The impact of the language statement is considered in connection with the support of multiple robot coordination. Requirements for a general-purpose robot control language are summarized, and several industrial applications of multiple robot coordination are discussed. Three types of group motion and their programming impact are reviewed: simultaneous motion, coordinated motion, and independent motion. Multitasking is also shown to be a necessary programming tool in multiple robot control. >

Reinforcement learning approach to generate goal-directed locomotion of a snake-like robot with screw-drive units

Abstract: In this paper we apply a policy improvement algorithm called Policy Improvement with Path Integrals (PI2) to generate goal-directed locomotion of a complex snake-like robot with screw-drive units. PI2 is numerically simple and has an ability to deal with high dimensional systems. Here, this approach is used to find proper locomotion control parameters, like joint angles and screw-drive velocities, of the robot. The learning process was achieved using a simulated robot and the learned parameters were successfully transferred to the real one. As a result the robot can locomote toward a given goal.

Impedance control of a bio-inspired flying and adhesion robot

Abstract: Endurance is a critical problem that most flying robots will definitely encounter. Inspired by flying animals in nature that take frequent short flights with periods of perching in between, we propose an innovative mechanism with flying and adhesion to solve this problem. Previously, we have developed some prototypes of flying and adhesion robots. However, when the robots switch between flying and adhesion, it is difficult to control the contact force; moreover, the robots could be damaged because of the abnormal contact with the environment. Therefore, we propose an impedance control approach for bio-inspired flying and adhesion robots to have smooth contact with the environment. The dynamic model of a bio-inspired robot is described, and the proposed impedance control method is applied to regulate the contact force with the environment. The bio-inspired flying and adhesion robot performs several phases of desired missions in the sequential manner. Firstly, the robot performs position control to approach the desired perch position. Secondly, the robot contacts with the environment and regulate the contact force. Both simulation and experiments were performed to validate the proposed method. The results verified the feasibility of the proposed control methods in controlling a bio-inspired flying and adhesion robot.