Geir Hovland

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A new approach to skill acquisition in assembly is proposed. An assembly skill is represented by a hybrid dynamic system where a discrete event controller models the skill at the task level. The output of the discrete event controller provides the reference commands for the underlying robot controller. This structure is naturally encoded by a hidden Markov(More)
This paper presents a new error kinematic model containing twelve parameters for the three linear actuators of the Gantry-Tau parallel kinematic manipulator. Three different types of measurement equipment, laser interferometers, linear encoders and double-ball bars, can successfully be used to calibrate the linear actuators. A method for selecting an(More)
Discrete event recognition based on force measurements in the frequency-domain is presented. The force signals arise from interaction between the workpiece and the environment in a planar assembly task. The discrete events are modeled as Hidden Markov Models (HMMs), where the models are trained oo-line with the Baum-Welch re-estimation algorithm. After the(More)
One of the main advantages of the Gantry-Tau machine is a large accessible workspace/footprint ratio compared to many other parallel machines. The Gantry-Tau improves this ration further by allowing a change of assembly mode without internal link collisions or collisions between the links and end-effector. The reconfigurable Gantry-Tau kinematic design(More)
The problem of controlling sensory input and perception for use in mobile navigation is addressed in this paper. The proposed solution offers several advantages compared with existing methods in the literature. First, the proposed solution is based on a stochastic dynamic-programming algorithm that guarantees cost efficiency of the real-time(More)
In this paper the invited session and the 4 original contributions are described first. Then the details of the first paper in the invited session is presented. In this first paper a new method for calculating the dynamic stiffness (frequency response) of parallel kinematic machines (PKMs) with six links, or Hexapods, is presented. The method assumes that(More)
A process monitor for robotic assembly based on hidden Markov models (HMMs) is presented. The HMM process monitor is based on the dynamic force/torque signals arising from interaction between the workpiece and the environment. The HMMs represent a stochastic, knowledge-based system in which the models are trained off-line with the Baum-Welch reestimation(More)