Robot control

About: Robot control is a research topic. Over the lifetime, 35264 publications have been published within this topic receiving 578821 citations. The topic is also known as: robotic control.

Sensory requirements and performance assessment of tele-presence controlled robots

Abstract: Robots have most successfully been applied in repetitive operations, but often when the task involves complex variable operations in unstructured environments teleoperation is preferred. As the complexity of these human supervisory tasks has increased the trend has been towards greater sensory feedback and more intuitive input control. This paper reports on the relative effectiveness of and need for sensory feedback systems for operator control in telepresence applications. In particular, studies were made of the performance of manipulation and navigation planning operations on a twin armed mobile robot using a variety of visual and audio cues and input systems. The performance was measured by experimentation with a range of subjects at a number of difficulty levels to test the effectiveness of the telepresence controller in a series of technical scenarios.

The design of adaptable indoor pipeline inspection robots

Abstract: This paper emphasizes the most representative contributions of the authors regarding the minirobotic systems. Thus, in the first part of the paper we have a classification of the in-pipe robots and a presentation of three modular in-pipe robotic systems for inspection and exploration. In the second part, a few new models of microrobotic in-pipe modular systems are described.

Experimental implementation of neural network controller for robot undergoing large payload changes

Abstract: A robot controller based on artificial neural networks (ANNs) is presented which is capable of compensating for changing payload masses. Two different feedforward (multilayer) neural networks are used to generate the inverse dynamics and to estimate the payload mass of a two-link planar manipulator. The inverse dynamics ANN receives the same input signals as a conventional computed torque controller as well as the payload mass estimate. By using a separate ANN to generate the payload mass estimate, both ANNs can be trained off-line. The proposed neural network architecture is implemented on actual hardware using a neurocomputer. Experimental results indicate that the ANN-based controller is able to capture the nonlinear dynamics of the actual manipulator. The ANN mass estimator responds very quickly to changing payloads. >

From Unknown Sensors and Actuators to Visually Guided Movement

Abstract: This paper describes a developmental system implemented on a real robot that learns a model of its own sensory and actuator apparatuses. There is no innate knowledge regarding the modality or representation of the sensoric input and the actuators, and the system relies on generic properties of the robot's world such as piecewise smooth effects of movement on sensory changes. The robot develops the model of its sensorimotor system by first performing random movements to create an informational map of the sensors. Using this map the robot then learns what effects the different possible actions have on the sensors. After this developmental process the robot can perform simple motion tracking

Robot controlling method for preventing collision of the robot with man

Abstract: PURPOSE:To achieve complete automatization of operation of a robot, by laying a load mat in the operable range of robot for detecting the position of a man who walks on the mat, and defining a danger region for making the robot act to meet with the special situation.