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In this paper we present a novel approach to human-robot control. Taking inspiration from Behaviour Based robotics and self-organisation principles, we present an interfacing mechanism, named KURE in this paper, with the ability to adapt both towards the user and the robotic morphology. The aim is for a transparent mechanism connecting user and robot, allowing for a seamless integration of control...
In this study, a robot arm that can imitate human arm is designed and presented. The potentiometers are located to the joints of the human arm in order to detect movements of human gestures, and data were collected by this way. The collected data named as “movement of human arm” are classified by the help of Artificial Neural Network (ANN). The robot performs its movements according to the classified...
Multisensor data fusion is highly applicable in robotics applications because the relationships among objects and events changes due to the change in orientation of robot, snag in sensory information, sensor range and environmental conditions etc. High level and low level image processing in machine vision are widely involved to investigate object identification in complex application. Due to the...
Smart sensing of environmental parameters is an important task in robotics, process industries, sensor networks and autonomous systems. In this paper, we propose a novel Chebyshev neural network (ChNN) to develop smart sensors which can provide linearized and accurate readout, and can compensate for nonlinear environmental disturbances including additive noise. By taking two environmental models and...
The future of robotics is not limited to factories and homes, and is extending to robot-assisted urban search and rescue. This paper proposes a new application of neural networks in this emerging field of research. Specifically, a neural network with feedforward architecture using the backpropagation learning algorithm is implemented in order to determine the positioning of a robotic gripper that...
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