8 citations · 16 across the 18 of their papers we have counts for
14 papers · 1 filter
Learning Unions of Convex Sets via Invertible Latent Decomposition for Path Planning
Taerim Yoon, Dongho Kang, Kisang Park +3
Collision-free path planning in cluttered, real-world environments relies on a representation of the collision-free space, and existing representations broadly fall into two catego…
Beyond Binary: Sim-to-Real Dexterous Manipulation with Physics-Grounded Contact Representation
Jiahe Pan, Stelian Coros, Jitendra Malik +1
A primary bottleneck in contact-rich manipulation is the difficulty of collecting real-world data. Sim-to-real reinforcement learning offers a scalable alternative, but the simulat…
Differentiable Environment-Trajectory Co-Optimization for Safe Multi-Agent Navigation
Zhan Gao, Gabriele Fadini, Stelian Coros +1
The environment plays a critical role in multi-agent navigation by imposing spatial constraints, rules, and limitations that agents must navigate around. Traditional approaches tre…
Teaching Robots Like Dogs: Learning Agile Navigation from Luring, Gesture, and Speech
Taerim Yoon, Dongho Kang, Jin Cheng +5
In this work, we aim to enable legged robots to learn how to interpret human social cues and produce appropriate behaviors through physical human guidance. However, learning throug…
Multi-Domain Motion Embedding: Expressive Real-Time Mimicry for Legged Robots
Matthias Heyrman, Chenhao Li, Victor Klemm +3
Effective motion representation is crucial for enabling robots to imitate expressive behaviors in real time, yet existing motion controllers often ignore inherent patterns in motio…
Whole-Body Inverse Dynamics MPC for Legged Loco-Manipulation
Lukas Molnar, Jin Cheng, Gabriele Fadini +3
Loco-manipulation demands coordinated whole-body motion to manipulate objects effectively while maintaining locomotion stability, presenting significant challenges for both plannin…