Search papers, labs, and topics across Lattice.
6
0
6
4
Integration of diverse robot policies can be streamlined from hours to minutes, revolutionizing how we deploy and evaluate robotic systems.
HERO enables robots to autonomously evolve manipulation skills from scratch, drastically reducing reliance on human demonstrations.
RxBrain achieves a groundbreaking integration of language and visual reasoning, enabling agents to generate embodied plans that seamlessly connect abstract tasks with physical actions.
Shifting the focus from marginal probabilities to joint trajectory probabilities, dVLA-RL achieves unprecedented success rates in robotic manipulation tasks.
LLM agents struggle to maintain performance in multi-day collaborative tasks, dropping significantly after just one environmental update, revealing a critical gap in adaptation to evolving real-world conditions.
Decoupling high-level VLM planning from low-level diffusion-based control lets robots reason like foundation models *and* execute precisely, outperforming end-to-end approaches in complex manipulation tasks.
