Vision Aided Dynamic Exploration of Unstructured Terrain with a Small-Scale Quadruped Robot
Name
2020_ICRA_Vision.pdf
Description
Accepted version
Size
5.98 MB
Format
Unknown
Checksum (MD5)
8c1e262b37f930b008a2df82186d0380
Author(s)
Kim, D.
Carballo, Daniel(Daniel A.)
DiCarlo, James
Katz, Boris
Bledt, Gerardo
Lim, B.
Kim, Songmin
Date Issued
2020
Journal
2020 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Kim, D, Carballo, D, Di Carlo, J, Katz, B, Bledt, G et al. 2020. "Vision Aided Dynamic Exploration of Unstructured Terrain with a Small-Scale Quadruped Robot." 2020 IEEE International Conference on Robotics and Automation (ICRA).
Version
Author's final manuscript
Abstract
Abstract— Legged robots have been highlighted as promising
mobile platforms for disaster response and rescue scenarios because of their rough terrain locomotion capability. In
cluttered environments, small robots are desirable as they
can maneuver through small gaps, narrow paths, or tunnels.
However small robots have their own set of difficulties such as
limited space for sensors, limited obstacle clearance, and scaleddown walking speed. In this paper, we extensively address
these difficulties via effective sensor integration and exploitation
of dynamic locomotion and jumping. We integrate two Intel
RealSense sensors into the MIT Mini-Cheetah, a 0.3 m tall, 9 kg
quadruped robot. Simple and effective filtering and evaluation
algorithms are used for foothold adjustment and obstacle
avoidance. We showcase the exploration of highly irregular
terrain using dynamic trotting and jumping with the smallscale, fully sensorized Mini-Cheetah quadruped robot.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICRA40945.2020.9196777
