Articulated robot

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

Redundant robot control for higher flexibility

Abstract: The joint velocities required to move the robot end-effector with a desired speed depend on the direction of motion. Robot's mobility, i.e., its ability to move, is better in the directions requiring lower joint velocities. When the robot is near a singularity configuration, the joint velocities required to attain the end-effector velocity in certain directions are extremely high. Thus arbitrary directional changes become more difficult. Robot's flexibility, defined as its ability to change the direction of the end-effector motion, is low in the vicinity of singular configurations. Addition of redundant joints can greatly enhance their flexibility. However, this requires a proper utilization of redundancy. A control scheme is presented to improve the flexibility of redundant robots. The feasibility and effectiveness of this control scheme are demonstrated through simulation.

Statically-balanced direct-drive robot arm

Abstract: A robot (10) includes a statically-balanced direct-drive arm (14) having three degrees of freedom, all of which are independent articulated drive joints, the driving axes of two of which intersect at the center of gravity of the arm to eliminate gravity forces on the drive system without counterweights.

Human direct teaching of industrial articulated robot arms based on force-free control

Abstract: Force-free control produces motion in a robot arm as if it were under conditions with no gravity and no friction. In this study, a method of force-free control is proposed for industrial articulated robot arms. The force-free control proposed was applied to the direct teaching of industrial articulated robot arms in that the robot arm was moved by direct human force. Generally, the teaching of industrial articulated robot arms is carried out using operational equipment called a teach-pendant. Smooth teaching can be achieved if direct teaching is applicable. The force-free control proposed enables humans to teach industrial articulated robot arms directly. The effectiveness of force-free control was confirmed by experimental work on an articulated robot arm with two degrees of freedom.

Anthrob - A printed anthropomimetic robot

Abstract: Anthropomimetic robotics differ from conventional approaches by capitalizing on the replication of the inner structures of the human body, such as muscles, tendons, bones and joints [1]. Prominent examples for this class of robots are the robots developed at the JSK laboratory of the University of Tokyo and the robots developed by the EU-funded project Embodied Cognition in a Compliantly Engineered Robot (Eccerobot). However, the high complexity of these robots as well as their lack of sensors has so far failed to provide the desired new insights in the field of control. Therefore, we developed the simplified but sensorized robot Anthrob. The robot replicates the human upper limb and features 13 compliant tendon driven uni- and biarticular muscles as well as a spherical shoulder joint. Whenever possible, Selective Laser Sintering (SLS) was used for the production of the robot parts to reduce the production costs and to implement cutting-edge technologies, such as tendon canals or solid-state joints.

Locomotion control system for legged mobile robot

Abstract: A locomotion control system of a biped walking robot having a body and two articulated legs including ankle joints and connected to the body. A mathematical model is predesigned to approximate the robot. The mathematical model is assumed to have ideal rigidity and based on the model target angles of the joints including the ankle joints are preestablished in advance. Robot joints are provided with servo motors and control values are determined on the basis of the target joint angles to drive the servo motors to follow the target joint angles. A sensor is provided to detect moment acting on the ankle joints or the legs. The detected moment is multiplied by a gain made up of the reciprocal number of the amount of rigidity of the ankle joints. And based on the product, the control value is corrected so as to compensate the deformation. As a result, the discrepancy between the model and the actual robot is compensated so that, not only the robot can walk more stably, but the freedom of possible compliance control can be increased. Moreover, the legs can have low weight and inertia so that the walking stability can be further enhanced.