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BALLU2: A Safe and Affordable Buoyancy Assisted Biped
Hosik Chae1, Min Sung Ahn1, Donghun Noh1
1Robotics and Mechanisms Laboratory (RoMeLa), Department of Mechanical and Aerospace Engineering, University of California, Los Angeles (UCLA), Los Angeles, CA, United States.
Frontiers in Robotics and AI
|December 27, 2021
Summary
This study introduces the Buoyancy Assisted Lightweight Legged Unit (BALLU), a robot designed never to fall. A novel data-driven controller enables stable walking, demonstrating robustness in simulations and real-world tests.
Area of Science:
- Robotics
- Control Systems
- Artificial Intelligence
Background:
- Current legged robots face challenges operating near humans due to stability and safety concerns.
- Buoyancy offers a novel solution to enhance robot stability and safety.
- The unique dynamics of buoyancy-assisted robots present significant control challenges.
Purpose of the Study:
- To present the first full disclosure of the Buoyancy Assisted Lightweight Legged Unit (BALLU) concept and its implementation (BALLU2).
- To analyze the unique characteristics and challenges of BALLU's design.
- To develop and validate a data-driven walking controller for non-teleoperated locomotion.
Main Methods:
- Hardware design and implementation of BALLU2.
- Motion analysis to understand the robot's unique dynamics.
- A data-driven approach using Spearman Correlation Coefficient for state vector extraction and an artificial neural network for controller training.
Main Results:
- The proposed controller successfully generated periodic walking sequences in both simulation and real-world hardware.
- The controller demonstrated robustness by handling unseen conditions without additional transfer learning.
- The statistical process effectively extracted a low-dimensional state vector capturing essential high-dimensional dynamics.
Conclusions:
- BALLU offers a promising approach to creating safer, more stable legged robots for human-robot interaction.
- The developed data-driven controller is effective and robust for BALLU's unique locomotion.
- The methodology for state vector extraction is efficient for complex robotic systems.
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