8 papers · 1 filter
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…
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…
Mechanisms and Computational Design of Multi-Modal End-Effector with Force Sensing using Gated Networks
Yusuke Tanaka, Alvin Zhu, Richard Lin +2
In limbed robotics, end-effectors must serve dual functions, such as both feet for locomotion and grippers for grasping, which presents design challenges. This paper introduces a m…