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Barrett Heyneman

Researcher at Stanford University

Publications -  13
Citations -  1297

Barrett Heyneman is an academic researcher from Stanford University. The author has contributed to research in topics: Tactile sensor & Climbing. The author has an hindex of 9, co-authored 13 publications receiving 1147 citations.

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Journal ArticleDOI

Smooth Vertical Surface Climbing With Directional Adhesion

TL;DR: The design and fabrication methods used to create underactuated, multimaterial structures that conform to surfaces over a range of length scales from centimeters to micrometers are described.
Proceedings ArticleDOI

Whole body adhesion: hierarchical, directional and distributed control of adhesive forces for a climbing robot

TL;DR: The design and control of a new bio-inspired climbing robot designed to scale smooth vertical surfaces using directional adhesive materials, called Stickybot, draws its inspiration from geckos and other climbing lizards and employs similar compliance and force control strategies to climb smooth Vertical surfaces including glass, tile and plastic panels.
Journal ArticleDOI

Design and testing of a selectively compliant underactuated hand

TL;DR: A compliant underactuated hand, capable of locking individual joints, has been developed that can adopt configurations and grasp sequences that would otherwise require a fully actuated solution.
Proceedings ArticleDOI

Climbing rough vertical surfaces with hierarchical directional adhesion

TL;DR: A four legged robot that was previously restricted to climbing smooth surfaces is able to climb vertical surfaces such as a wood panels, painted metals, and plastics using a new two-tiered directional adhesive system that improves adhesion by a factor of five compared to the wedge features alone.
Proceedings ArticleDOI

Gecko-inspired climbing behaviors on vertical and overhanging surfaces

TL;DR: The empirically derived limit surface for directional adhesive pads is convex, which permits efficient computation of the desired internal and external forces among the feet to maximize a safety margin with respect to disturbance forces on the robot.