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OBJECTIVE To develop a model for human performance in combined translational and rotational movements based on Fitts' law. BACKGROUND Fitts' law has been successfully applied to translational movements in the past, providing generalization beyond a specific task as well as performance predictions. For movements involving both translations and rotations,(More)
New mobile robotic devices are conquering homes. From automatic shades to motorized vacuum cleaning units, advanced technologies are progressively being introduced into real domestic home environments. Technology is no longer being introduced to simply serve information or environmental control. Dynamic and mobile elements are being introduced to perform(More)
Assistive robots are increasingly being envisioned as an aid to the elderly and disabled. However controlling a robotic system with a potentially large amount of Degrees of Freedom (DOF) in a safe and reliable way is not an easy task, even without limitations in the mobility of the upper extremities. Shared control has been proposed as a way of aiding(More)
An approach for adaptive shared control of an assistive manipulator is presented. A set of distributed collision and proximity sensors is used to aid in limiting collisions during direct control by the disabled user. Artificial neural networks adapt the use of the proximity sensors online, which limits movements in the direction of an obstacle before a(More)
The work described here explores a neural network architecture that can be embedded directly in the realtime sensorimotor coordination loop of a developmental robot platform. We take inspiration from the way children are able to learn while interacting with a teacher, in particular the use of prediction of the teacher actions to improve own learning. The(More)
One of the grand challenges for the robotics community is to create robots that operate robustly in realworld scenarios. Most current robots are limited to factories, laboratories or similar controlled settings. This contrasts with the seeming ease with which insects, animals and humans handle uncertainty, dynamic events and complexity. Assistive robots are(More)
The work described here explores an approach for learning online the sensorimotor interaction that a robot has with the world, and the higher-level concepts grounded in this interaction. A type of spatiotemporal connectionist neural network was implemented. In consists of a set of time-delayed input layers which receive both low-level sensor inputs and(More)