Ashwin Dani

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We present an algorithm to learn human arm motion from demonstrations and infer the goal location (intention) of human reaching actions. To capture the complexity of human arm reaching motion, an artificial neural network (ANN) is used to represent the arm motion dynamics. The trajectories of the arm motion for reaching operation are modeled as stable(More)
In this paper, we present an algorithm to infer the intent of a human operator's arm movements based on the observations from a Microsoft Kinect sensor. Intentions are modeled as goal locations in 3-dimensional (3D) space where the human is intending to reach. Human intention inference is a critical step towards realizing safe human-robot collaboration.(More)
An efficient gyro-aided iterative Earth Mover's Distance (iEMD) algorithm for visual tracking is proposed in this paper. The Earth Mover's Distance (EMD) is used as the similarity measure to search the optimal template candidates in color-spatial space in a video sequence. The computation of the EMD is formulated as the transportation problem from linear(More)
An algorithm called gaze-based multiple model intention estimator (G-MMIE) is presented for early prediction of the goal location (intention) of human reaching actions. To capture the complexity of human arm reaching motion, a neural network (NN) is used to represent the arm motion dynamics. The trajectories of the arm motion for reaching tasks are modeled(More)
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