Demo Data from EDBT 2026 / reviewers in the wild / expert
Sam Castellanos
dblp:226/6311 · also Samantha Castellanos
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2020
—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
2 papers |
Legged, aerial and field robots · 82% Robot manipulation · 18% | |
| Human-computer interaction and pervasive computing
1 paper |
Personal fabrication and tangible interfaces · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots › legged robots
legged robot locomotion |
0.4 | 1 | 2020 | Scaling down an insect-size microrobot, HAMR-VI into HAMR-Jr · ICRA 2020 |
Robotics › Legged, aerial and field robots › mobile robot locomotion
microrobot locomotion |
0.4 | 1 | 2020 | Scaling down an insect-size microrobot, HAMR-VI into HAMR-Jr · ICRA 2020 |
Personal fabrication and tangible interfaces
soft robotics |
0.3 | 1 | 2018 | Compliant Low Profile Multi-Axis Force Sensors · ICRA 2018 |
Robotics › Robot manipulation
grasping |
0.1 | 1 | 2018 | Compliant Low Profile Multi-Axis Force Sensors · ICRA 2018 |
Robotics › Robot manipulation › grasping
soft gripper |
0.1 | 1 | 2018 | Compliant Low Profile Multi-Axis Force Sensors · ICRA 2018 |
Methods — techniques the papers use, named apart from their topics
laser machining · 0.7elastomer encapsulation · 0.7carbon fiber composite · 0.7open-loop locomotion characterization · 0.4design and fabrication · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Scaling down an insect-size microrobot, HAMR-VI into HAMR-JrabstractHere 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 |
ICRA | 3 |
| 2018 | Compliant Low Profile Multi-Axis Force SensorsabstractThe development of soft, compliant force sensors is greatly sought after in areas such as soft robotics and prosthetics. Nevertheless, solutions for measuring forces in multiple axes, while being mechanically compliant, have been few and far between. Here we present a compliant sensor able to detect forces tangential and normal to the sensor surface. The transduction mechanism is based on the deformation of laser-machined carbon fiber composite (CFC) micro-scale meanders, encapsulated within elastomers layers. Strains in the elastomer are transmitted to the meanders, causing changes in the electrical resistance of the sensor contact mechanics. Configuring the meanders in a radial pattern, segmenting them into quadrants (two antagonist pairs) and biasing the center of the sensor out-of-plane enables detection of forces in multiple axis via differential measurement. Sensors were manufactured using a custom fabrication process and exhibited high mechanical compliance with a very low form factor. The sensors were experimentally characterized and demonstrated large differential changes in resistance (up to 26 kΩ for tangential forces applied to the sensor surface). We integrated our sensor onto a soft robotic gripper finger and demonstrated the ability to detect changes in friction at the actuator surface, thus demonstrating their potential for real world applications. Oluwaseun A. Araromi, Sam Castellanos, Conor J. Walsh, Robert J. Wood |
ICRA | 2 |