8 papers
Sampling Strategies for Robust Universal Quadrupedal Locomotion Policies
David Rytz, Kim Tien Ly, Ioannis Havoutis
This work focuses on sampling strategies of configuration variations for generating robust universal locomotion policies for quadrupedal robots. We investigate the effects of sampl…
PlatoLTL: Learning to Generalize Across Symbols in LTL Instructions for Multi-Task RL
Jacques Cloete, Mathias Jackermeier, Ioannis Havoutis +1
A central challenge in multi-task reinforcement learning (RL) is to train generalist policies capable of performing tasks not seen during training. To facilitate such generalizatio…
MetaSym: A Symplectic Meta-learning Framework for Physical Intelligence
Pranav Vaidhyanathan, Aristotelis Papatheodorou, Mark T. Mitchison +2
Scalable and generalizable physics-aware deep learning has long been considered a significant challenge with various applications across diverse domains ranging from robotics to mo…
InteLiPlan: An Interactive Lightweight LLM-Based Planner for Domestic Robot Autonomy
Kim Tien Ly, Kai Lu, Ioannis Havoutis
We introduce an interactive LLM-based framework designed to enhance the autonomy and robustness of domestic robots, targeting embodied intelligence. Our approach reduces reliance o…
Vision-Language-Policy Model for Dynamic Robot Task Planning
Jin Wang, Kim Tien Ly, Jacques Cloete +3
Bridging the gap between natural language commands and autonomous execution in unstructured environments remains an open challenge for robotics. This requires robots to perceive an…
RAKOMO: Reachability-Aware K-Order Markov Path Optimization for Quadrupedal Loco-Manipulation
Mattia Risiglione, Abdelrahman Abdalla, Victor Barasuol +3
Legged manipulators, such as quadrupeds equipped with robotic arms, require motion planning techniques that account for their complex kinematic constraints in order to perform mani…