4 citations · 4 across the 6 of their papers we have counts for
8 papers
FARO: Feasibility-Aware Robot Motion Optimization
Michal Ciebielski, Shafeef Omar, Aaron Johnson +1
Fast planning of novel behaviors in unseen scenarios remains a fundamental challenge in robotics. The high-dimensional, hybrid, and underactuated nature of humanoid loco-manipulati…
Humanoid-DART: Humanoid Loco-Manipulation using Diffusion-guided Augmentation through Relabeling and Tracking
Pranav Debbad, Kanish Thiagarajan, Victor Dhédin +2
Imitating human demonstrations has emerged as a dominant paradigm for learning humanoid loco-manipulation policies. However, scaling these approaches remains challenging due to the…
MotionDisco: Motion Discovery for Extreme Humanoid Loco-Manipulation
Ilyass Taouil, Michal Ciebelski, Shafeef Omar +4
We present MotionDisco, a framework that discovers contact-rich, long-horizon humanoid loco-manipulation motions from scratch, without relying on teleoperation or motion retargetin…
SLowRL: Safe Low-Rank Adaptation Reinforcement Learning for Locomotion
Elham Daneshmand, Shafeef Omar, Glen Berseth +2
Sim-to-real transfer of locomotion policies often leads to performance degradation due to the inevitable sim-to-real gap. Naively fine-tuning these policies directly on hardware is…
DynaRetarget: Dynamically-Feasible Retargeting using Sampling-Based Trajectory Optimization
Victor Dhedin, Ilyass Taouil, Shafeef Omar +4
In this paper, we introduce DynaRetarget, a complete pipeline for retargeting human motions to humanoid control policies. The core component of DynaRetarget is a novel Sampling-Bas…
Learning to Act Through Contact: A Unified View of Multi-Task Robot Learning
Shafeef Omar, Majid Khadiv
We present a unified framework for multi-task locomotion and manipulation policy learning grounded in a contact-explicit representation. Instead of designing different policies for…
Fast Convex Visual Foothold Adaptation for Quadrupedal Locomotion
Shafeef Omar, Lorenzo Amatucci, Giulio Turrisi +2
This extended abstract provides a short introduction on our recently developed perception-based controller for quadrupedal locomotion. Compared to our previous approach based on Vi…
SafeSteps: Learning Safer Footstep Planning Policies for Legged Robots via Model-Based Priors
Shafeef Omar, Lorenzo Amatucci, Victor Barasuol +2
We present a footstep planning policy for quadrupedal locomotion that is able to directly take into consideration a-priori safety information in its decisions. At its core, a learn…