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Andrew K. Schulz

dblp:364/4123 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021

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 · 87% Robot manipulation · 13%
Computer graphics and multimedia
1 paper
Computer animation and physical simulation · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
hopping robot
0.912025
Materials Matter: Investigating Functional Advantages of Bio-Inspired Materials via Simulated Robotic Hopping · ICRA 2025
Robotics › Legged, aerial and field robots › legged robots
legged robot locomotion
0.912025
Materials Matter: Investigating Functional Advantages of Bio-Inspired Materials via Simulated Robotic Hopping · ICRA 2025
Robotics › Robot manipulation › robot design
bio-inspired robot design
0.312025
Materials Matter: Investigating Functional Advantages of Bio-Inspired Materials via Simulated Robotic Hopping · ICRA 2025

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

rigid body dynamics · 1.7material gradient simulation · 1.7
YearPublicationVenuePosition
2025 Materials Matter: Investigating Functional Advantages of Bio-Inspired Materials via Simulated Robotic Hopping
abstract
In contrast with the diversity of materials found in nature, most robots are designed with some combination of aluminum, stainless steel, and 3D-printed filament. Additionally, robotic systems are typically assumed to follow basic rigid-body dynamics. However, several examples in nature illustrate how changes in physical material properties yield functional advantages. In this paper, we explore how physical materials (non-rigid bodies) affect the functional performance of a hopping robot. In doing so, we address the practical question of how to model and simulate material properties. Through these simulations we demonstrate that material gradients in the leg of a single-limb hopper provide functional advantages compared to homogeneous designs. For example, when considering incline ramp hopping, a material gradient with increasing density provides a 35% reduction in tracking error and a 23% reduction in power consumption compared to homogeneous stainless steel. By providing bio-inspiration to the rigid limbs in a robotic system, we seek to show that future fabrication of robots should look to leverage the material anisotropies of moduli and density found in nature. This would allow for reduced vibrations in the system and would provide offsets of joint torques and vibrations while protecting their structural integrity against reduced fatigue and wear. This simulation system could inspire future intelligent material gradients of custom-fabricated robotic locomotive devices.
Andrew K. Schulz, Ayah G. Ahmad, Maegan Tucker
ICRA1