Abstract: We present a scalable framework for cross-embodiment humanoid robot control by learning a shared latent representation that unifies motion across humans and diverse humanoid platforms, including single-arm, dual-arm, and legged humanoid robots. Our method proceeds in two stages. First, we construct a decoupled latent space that captures localized motion patterns … [Read more...] about Cross-Embodiment Imitation: Learning a Unified Latent Space for Multirobot Control
Features
DAPPER: Discriminability-Aware Policy-to-Policy Preference-Based Reinforcement Learning for Query-Efficient Robot Skill Acquisition
Abstract: Preference-based reinforcement learning (PBRL) enables policy learning through simple queries comparing trajectories from a single policy. While human responses to these queries make it possible to learn policies aligned with human preferences, PBRL suffers from low query efficiency, as policy bias limits trajectory diversity and reduces the number of … [Read more...] about DAPPER: Discriminability-Aware Policy-to-Policy Preference-Based Reinforcement Learning for Query-Efficient Robot Skill Acquisition
Real-Time Generation of Near Minimum-Energy Trajectories via Constraint-Informed Residual Learning: A Paradigm for Learning From Optimal Solutions
Abstract: Industrial robotics demands significant energy to operate, making energy-reduction methodologies increasingly important. Strategies for planning minimum-energy trajectories typically involve solving nonlinear optimal control problems (OCPs), which rarely cope with real-time (RT) requirements. In this article, we propose a paradigm for generating near … [Read more...] about Real-Time Generation of Near Minimum-Energy Trajectories via Constraint-Informed Residual Learning: A Paradigm for Learning From Optimal Solutions
Sequentially Teaching Sequential Tasks (ST)2: Teaching Robots Long-Horizon Manipulation Skills
Abstract: Learning from demonstration (LfD) has proved useful for teaching robots complex skills with high sample efficiency. However, teaching long-horizon tasks with multiple skills is challenging as deviations tend to accumulate, the distributional shift becomes more evident, and human teachers become fatigued over time, thereby increasing the likelihood of failure. To … [Read more...] about Sequentially Teaching Sequential Tasks (ST)2: Teaching Robots Long-Horizon Manipulation Skills
Simplifying Data-Driven Modeling of the Volume–Flow–Pressure Relationship in Hydraulic Soft Robotic Actuators: A Practical and Balanced Solution
Abstract: Soft robotic systems are known for their flexibility and adaptability, but traditional physics-based models struggle to capture their complex, nonlinear behaviors. This study explores a data-driven approach to modeling the volume–flow–pressure relationship in hydraulic soft actuators, focusing on low-complexity models with high accuracy. We perform regression … [Read more...] about Simplifying Data-Driven Modeling of the Volume–Flow–Pressure Relationship in Hydraulic Soft Robotic Actuators: A Practical and Balanced Solution
