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Nicholas W. Bartlett

dblp:153/7482 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › actuator design
pneumatic actuation
0.312017
Tunable friction through constrained inflation of an elastomeric membrane · ICRA 2017
Robotics › Robot manipulation
soft robotics
0.312017
Tunable friction through constrained inflation of an elastomeric membrane · ICRA 2017
Robotics › Robot manipulation › grasping
soft gripper
0.112017
Tunable friction through constrained inflation of an elastomeric membrane · ICRA 2017

Methods — techniques the papers use, named apart from their topics

pneumatic actuation · 0.3force characterization · 0.3
YearPublicationVenuePosition
2017 Tunable friction through constrained inflation of an elastomeric membrane
abstract
Many areas of robotics, particularly locomotion and grasping, can benefit from the ability to modulate friction on surfaces that come into contact with objects in the environment. Previous research has tried to address the challenge of tunable friction; however, those efforts only provide modest gains or are difficult to integrate. We propose a tunable friction mechanism that relies on pneumatic actuation and is easily integrated into pre-existing soft actuators. We characterize the performance of our friction mechanism with quantitative force data for varying preload forces, substrate materials, and inflation pressures. Testing results show that our tunable friction mechanism achieves an order of magnitude differentiation in friction forces between high and low friction states. We demonstrate its potential application in a one degree-of-freedom soft crawler and a soft gripper with actuatable finger friction pads. The crawler successfully propelled itself forward by leveraging asymmetric strokes and the gripper achieved a factor of five differentiation of grip force between engaged and disengaged states of the friction tuning mechanism.
Kaitlyn P. Becker, Nicholas W. Bartlett, Melinda J. D. Malley, Peter M. Kjeer, Robert J. Wood
ICRA2
2014 An untethered jumping soft robot
abstract
Locomoting soft robots typically walk or crawl slowly relative to their rigid counterparts. In order to execute agile behaviors such as jumping, rapid actuation modes are required. Here we present an untethered soft-bodied robot that uses a combination of pneumatic and explosive actuators to execute directional jumping maneuvers. This robot can autonomously jump up to 0.6 meters laterally with an apex of up to 0.6 meters (7.5 times it's body height) and can achieve targeted jumping onto an object. The robot is able to execute these directed jumps while carrying the required fuel, pneumatics, control electronics, and battery. We also present a thermodynamic model for the combustion of butane used to power jumping, and calculate the theoretical maximum work output for the design. From experimental results, we find the mechanical efficiency of this prototype to be 0.8%.
Michael Thomas Tolley, Robert F. Shepherd, Michael Karpelson, Nicholas W. Bartlett, Kevin C. Galloway, Michael F. Wehner, Rui Nunes, George M. Whitesides, Robert J. Wood
IROS4