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Jennifer Shum

dblp:196/8400 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

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
Legged, aerial and field robots · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots › legged robots
legged robot locomotion
0.412020
Scaling down an insect-size microrobot, HAMR-VI into HAMR-Jr · ICRA 2020
Robotics › Legged, aerial and field robots › mobile robot locomotion
microrobot locomotion
0.412020
Scaling down an insect-size microrobot, HAMR-VI into HAMR-Jr · ICRA 2020

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

open-loop locomotion characterization · 0.4design and fabrication · 0.4
YearPublicationVenuePosition
2020 Scaling down an insect-size microrobot, HAMR-VI into HAMR-Jr
abstract
Here we present HAMR-Jr, a 22.5mm, 320mg quadrupedal microrobot. With eight independently actuated degrees of freedom, HAMR-Jr is, to our knowledge, the most mechanically dexterous legged robot at its scale and is capable of high-speed locomotion (13.91bodylengthss-1) at a variety of stride frequencies (1-200Hz) using multiple gaits. We achieved this using a design and fabrication process that is flexible, allowing scaling with minimum changes to our workflow. We further characterized HAMR-Jr's open-loop locomotion and compared it with the larger scale HAMR-VI microrobot to demonstrate the effectiveness of scaling laws in predicting running performance.
Kaushik Jayaram, Jennifer Shum, Sam Castellanos, E. Farrell Helbling, Robert J. Wood
ICRA2