Gray, Steven R
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Publication Toward tactilely transparent gloves: Collocated slip sensing and vibrotactile actuation(2009-04-03) Romano, Joseph M; Gray, Steven R; Jacobs, Nathan T; Kuchenbecker, Katherine JTactile information plays a critical role in the human ability to manipulate objects with one's hands. Many environments require the use of protective gloves that diminish essential tactile feedback. Under these circumstances, seemingly simple tasks such as picking up an object can become very difficult. This paper introduces the SlipGlove, a novel device that uses an advanced sensing and actuation system to return this vital tactile information to the user. Our SlipGlove prototypes focus on providing tactile cues associated with slip between the glove and a contact surface. Relative motion is sensed using optical mouse sensors embedded in the glove's surface. This information is conveyed to the wearer via miniature vibration motors placed inside the glove against the wearer's skin. The collocation of slip sensing and tactile feedback creates a system that is natural and intuitive to use. We report results from a human subject study demonstrating that the SlipGlove allows the wearer to approach the capabilities of bare skin in detecting and reacting to fingertip slip. Users of the SlipGlove also had significantly faster and more consistent reaction to fingertip slip when compared to a traditional glove design. The SlipGlove technology allows us to enhance human perception when interacting with real environments and move toward the goal of a tactilely transparent glove.Publication Motion Primitive-Based Graph Planning for Mobile Manipulation With Closed-Chain Systems(2012-01-01) Gray, Steven R; Clingerman, Christopher; Kumar, Vijay; Likhachev, MaximMotion primitive-based (lattice-based) graphs have been used extensively in navigation, but application to high-dimensional state-spaces has remained limited by computational complexity. In this work, we show how these graphs can be applied to mobile manipulation. The formation of closed chains in tasks that involve contacts with the environment may reduce the number of available degrees of freedom but add complexity in terms of constraints in the high-dimensional state space. We propose a novel method to reduce dimensionality by abstracting away the constraints associated with closed-chain systems. Proofs are introduced for the application to graph-search and its theoretical guarantees of optimality. The dimensionality-reduction is done in a manner that enables finding optimal solutions to low-dimensional problems which map to correspondingly optimal full-dimensional solutions. We demonstrate the usefulness of our method with simulation results; we apply our approach to moving an object in 2D using a mobile manipulation platform with a planar arm.