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Alexander H. Chang

6 accepted papers

2023

Multi-Gait Locomotion Planning and Tracking for Tendon-Actuated Terrestrial Soft Robot (TerreSoRo)

Arun Niddish Mahendran, Caitlin Freeman, Alexander H. Chang, Michael McDougall, Patricio A. Vela, Vishesh Vikas
IROS 2023poster

The adaptability of soft robots makes them ideal candidates to maneuver through unstructured environments. However, locomotion challenges arise due to complexities in modeling the body mechanics, actuation, and robot-environment dynamics. These factors contribute to the gap between their potential a…

Cited by 2Source ↗Scholar ↗
2021

Shape-centric Modeling for Soft Robot Inchworm Locomotion

Alexander H. Chang, Caitlin Freeman, Arun Niddish Mahendran, Vishesh Vikas, Patricio A. Vela
IROS 2021poster

Soft robot modeling tends to prioritize soft robot dynamics in order to recover how they might behave. Soft robot design tends to focus on how to use compliant elements with actuation to effect certain canonical movement profiles. For soft robot locomotors, these profiles should lead to locomotion.…

Cited by 10Source ↗Scholar ↗
2019

Every Hop is an Opportunity: Quickly Classifying and Adapting to Terrain During Targeted Hopping

Alexander H. Chang, Christian Hubicki, Aaron Ames, Patricio A. Vela
ICRA 2019poster

Practical use of robots in diverse domains requires programming for, or adapting to, each domain and its unique characteristics. Failure to do so compromises the ability of the robot to achieve task-relevant objectives. Here we describe how the learned terrain reaction force profiles of a hopping ro…

Cited by 13Source ↗Scholar ↗
2017

Closed-loop path following of traveling wave rectilinear motion through obstacle-strewn terrain

Alexander H. Chang, Patricio A. Vela
ICRA 2017poster

High-level, closed-loop traversal through obstacle-strewn environments remains an open and challenging endeavor for snake-like robotic platforms. Rectilinear forms of locomotion, despite their unique mobility advantages compared to other gait shapes, have seen relatively little progress toward this…

Cited by 7Source ↗Scholar ↗
2017

Learning to jump in granular media: Unifying optimal control synthesis with Gaussian process-based regression

Alexander H. Chang, Christian M. Hubicki, Jeff J. Aguilar, Daniel I. Goldman, Aaron D. Ames, Patricio A. Vela
ICRA 2017poster

The varied and complex dynamics of deformable terrain are significant impediments toward real-world viability of locomotive robotics, particularly for legged machines. We explore vertical jumping on granular media (GM) as a model task for legged locomotion on uncharacterized deformable terrain. By i…

Cited by 26Source ↗Scholar ↗
2015

Incorporating frictional anisotropy in the design of a robotic snake through the exploitation of scales

Miguel M. Serrano, Alexander H. Chang, Guangcong Zhang, Patricio A. Vela
ICRA 2015poster

The scales on the skin of a snake are an integral part of the snake's locomotive capabilities. It stands to reason that the integration of scales into the design of robotic snakes would open new properties to exploit. In this work, we present a robotic snake design that incorporates rigid scales in…

Cited by 30Source ↗Scholar ↗