Edinburgh Research Archive

In this chapter, we develop a new view on problems of movement control and planning from a Machine Learning perspective. In this view, decision making, control, and planning are all considered as an inference or (alternately) ...

Efficient human motor control is characterized by an extensive use of joint impedance modulation, which is achieved by co-contracting antagonistic muscles in a way that is beneficial to the specific task. While there is ...

Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the task or the environment. Constraints are usually not observable and frequently change between contexts. In ...

Dynamic movement primitives (DMPs) have been proposed as a powerful, robust and adaptive tool for planning robot trajectories based on demonstrated example movements. Adaptation of DMPs to new task requirements becomes ...

We consider the problem of tactile discrimination, with the goal of estimating an underlying state parameter in a sequential setting. If the data is continuous and high- dimensional, collecting enough representative data ...

We present a novel correspondence-based technique for efficient shape classification and retrieval. Shape boundaries are described by a set of (ad hoc) equally spaced points avoiding the need to extract landmark points. ...

We present a novel manipulandum for understanding the sensorimotor processes involved in object grasping. We have developed a closed-loop prosthetic hand, with 2 degrees of control and 32 channels of vibrotactile feedback ...

Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently change between contexts. In this paper, ...