Search results for: George I. Boutselis
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2016 IEEE 55th Conference on Decision and Control (CDC) > 2016 - 2022
We propose a novel methodology for stochastic trajectory optimization which is based on merging the theory of spectral expansions with Differential Dynamic Programming. Specifically, we employ polynomial chaos expansions to handle parametric uncertainties and utilize the Karhunen-Loéve transformation to represent stochastic forces. This allows us to build a generic framework and avoid relying on restrictive...
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In this paper a novel method towards solving the Stochastic Optimal Control problem is proposed, which is based on the combination of the generalized Polynomial Chaos theory and the Differential Dynamic Programming framework. Utilizing the Polynomial Chaos theory allows us to handle a wide range of uncertainties, without having to rely on limiting assumptions regarding the form of stochasticity. In...
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In this paper, we propose a complete methodology for deriving task-specific force closure grasps for multifingered robot hands under a wide range of uncertainties. Given a finite set of external disturbances representing the task to be executed, the concept of Q distance is introduced in a novel way to determine an efficient grasp with a task compatible hand posture (i.e., configuration and contact...
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The majority of the works on grasping consider both object as well as robot hand parameters to be accurately known and do not take into account the constraints imposed by the robot hand. In this paper, a complete methodology is proposed that handles the grasping problem under a wide range of uncertainties. Initially, we search for an acceptable posture that provides robustness against positioning...
