8 papers
Rapid co-design of Buoyancy-assisted robots for Challenging Locomotion using Gaussian Evolutionary Specialists
Ankit Sinha, Nitish Sontakke, Dennis Hong +2
Designing high-performance legged robots requires jointly optimizing morphology and control. Model-free Reinforcement Learning (RL) offers an alternative to model-predictive contro…
Symplectic Neural Operators for Learning Infinite Dimensional Hamiltonian Systems
Yeang Makara, Yusuke Tanaka, Takashi Matsubara +1
The modeling and simulation of infinite-dimensional Hamiltonian systems are central problems in mathematical physics and engineering, however they pose significant computational an…
AURA: Autonomous Upskilling with Retrieval-Augmented Agents
Alvin Zhu, Yusuke Tanaka, Andrew Goldberg +1
Designing reinforcement learning curricula for agile robots traditionally requires extensive manual tuning of reward functions, environment randomizations, and training configurati…
Mechanical Intelligence-Aware Curriculum Reinforcement Learning for Humanoids with Parallel Actuation
Yusuke Tanaka, Alvin Zhu, Quanyou Wang +2
Reinforcement learning (RL) has enabled advances in humanoid robot locomotion, yet most learning frameworks do not account for mechanical intelligence embedded in parallel actuatio…
Buoyant Choreographies: Harmonies of Light, Sound, and Human Connection
Dennis Hong, Yusuke Tanaka
BALLU, the Buoyancy Assisted Lightweight Legged Unit, is a unique legged robot with a helium balloon body and articulated legs \fig{fig:fig1}. Since it is buoyant-assisted, BALLU i…
Cycloidal Quasi-Direct Drive Actuator Designs with Learning-based Torque Estimation for Legged Robotics
Alvin Zhu, Yusuke Tanaka, Fadi Rafeedi +1
This paper presents a novel approach through the design and implementation of Cycloidal Quasi-Direct Drive actuators for legged robotics. The cycloidal gear mechanism, with its inh…