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cs.RO2024

URDF+: An Enhanced URDF for Robots with Kinematic Loops

Matthew Chignoli, Jean-Jacques Slotine, Patrick M. Wensing +1

Designs incorporating kinematic loops are becoming increasingly prevalent in the robotics community. Despite the existence of dynamics algorithms to deal with the effects of such l…

cs.RO2024

A Propagation Perspective on Recursive Forward Dynamics for Systems with Kinematic Loops

Matthew Chignoli, Nicholas Adrian, Sangbae Kim +1

We revisit the concept of constraint embedding as a means for dealing with kinematic loop constraints during dynamics computations for rigid-body systems. Specifically, we consider…

cs.RO2024

Learning Quadruped Locomotion Using Differentiable Simulation

Yunlong Song, Sangbae Kim, Davide Scaramuzza

This work explores the potential of using differentiable simulation for learning quadruped locomotion. Differentiable simulation promises fast convergence and stable training by co…

cs.RO2024

Tailoring Solution Accuracy for Fast Whole-body Model Predictive Control of Legged Robots

Charles Khazoom, Seungwoo Hong, Matthew Chignoli +2

Thanks to recent advancements in accelerating non-linear model predictive control (NMPC), it is now feasible to deploy whole-body NMPC at real-time rates for humanoid robots. Howev…

cs.RO2024

Probabilistic Homotopy Optimization for Dynamic Motion Planning

Shayan Pardis, Matthew Chignoli, Sangbae Kim

We present a homotopic approach to solving challenging, optimization-based motion planning problems. The approach uses Homotopy Optimization, which, unlike standard continuation me…

cs.RO2024

Integrating Model-Based Footstep Planning with Model-Free Reinforcement Learning for Dynamic Legged Locomotion

Ho Jae Lee, Seungwoo Hong, Sangbae Kim

In this work, we introduce a control framework that combines model-based footstep planning with Reinforcement Learning (RL), leveraging desired footstep patterns derived from the L…