Aaron M. Bestick

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We present a framework for parameter and state estimation of personalized human kinematic models from motion capture data. These models can be used to optimize a variety of human-robot collaboration scenarios for the comfort or ergonomics of an individual human collaborator. Our approach offers two main advantages over prior approaches from the literature(More)
In a game-theoretic framework, given parametric agent utility functions, we solve the inverse problem of computing the feasible set of utility function parameters for each individual agent, given that they play a correlated equilibrium strategy. We model agents as utility maximizers, then cast the problem of computing the parameters of players' utility(More)
We focus on selecting handover configurations that result in low human ergonomic cost not only at the time of handover, but also when the human is achieving a goal with the object after that handover. People take objects using whatever grasping configuration is most comfortable to them. When the human has a goal pose they’d like to place the object at,(More)
Human behavioral interventions aimed at improving health can benefit from objective wearable sensor data and mathematical models. Smartphone-based sensing is particularly practical for monitoring behavioral patterns because smartphones are fairly common, are carried by individuals throughout their daily lives, offer a variety of sensing modalities, and can(More)
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To truly make automation economical, there needs to be a shift in robotic performance: from highly specific at one task to general-purpose across many tasks. Unfortunately, such additional functionality is not cost-effective without a sacrifice in performance. In the case of robotics, it is a sacrifice in accuracy. This paper first investigates an industry(More)
The performance of human-robot collaboration tasks can be improved by incorporating predictions of the human collaborator's movement intentions. These predictions allow a collaborative robot to both provide appropriate assistance and plan its own motion so it does not interfere with the human. In the specific case of human reach intent prediction, prior(More)
In this paper, we present a capacitive sensor that measures the interfacial forces in prosthesis. The sensor's design, transfer function and performance metrics are tested and discussed. The sensor is uniquely able to measure both shear and normal stress simultaneously.
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