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Dynamic Movement Primitives (DMPs) are a generic approach for trajectory modeling in an attractor land-scape based on differential dynamical systems. DMPs guarantee stability and convergence properties of learned trajectories, and scale well to high dimensional data. In this paper, we propose DMP+, a modified formulation of DMPs which, while preserving the desirable properties of the original, 1)...
To study the neural mechanisms of fine crossed and fine uncrossed disparity in global stereopsis, event-related brain potentials(ERPs) were investigated by distinguishing depth. The crossed disparity of 6.54' and uncrossed disparity of 8.18' were selected. Results showed that there were no significant differences between ERPs to the stimuli with disparity of -8.18' and ERPs to the stimuli with disparity...
We consider the problem of representing and recognising tools, a subset of objects that have special functionality and action patterns. Our proposed framework is based on the biological evidence of hierarchical representation of tools in the region of the human cortex that generates action semantics. It addresses the shortfalls of traditional learning models of object representation applied on tools...
Theremin is an electronic musical instrument considered to be the most difficult to play which requires the player's hands to have high precision and stability as any position change within proximity of the instrument's antennae can make a difference to the pitch or volume. In a different direction to previous developments of Theremin playing robots, we propose a Humanoid Thereminist System that goes...
We consider the issue of segmenting an action in the learning phase into a logical set of smaller primitives in order to construct a generative model for imitation learning using a hierarchical approach. Our proposed framework, addressing the “how-to” question in imitation, is based on a one-shot imitation learning algorithm. It incorporates segmentation of a demonstrated template into a series of...
We propose a novel approach for robot movement imitation that is suitable for robotic arm movement in tasks such as reaching and grasping. This algorithm selects a previously observed path demonstrated by an agent and generates a path in a novel situation based on pairwise mapping of invariant feature locations present in both the demonstrated and the new scenes using minimum distortion and minimum...
The ability of autonomous navigation and adaptability to environment are key issues for the application of mobile robots in complex and unknown environments. A new method based on reinforcement learning and rough sets is proposed to accomplish robot navigation tasks in unknown environment. With reinforcement learning, robot can achieve autonomous navigation in an unknown environment. Because of the...
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