Search papers, labs, and topics across Lattice.
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Abandoning biased offline critics leads to more efficient online reinforcement learning, achieving superior performance on challenging tasks.
Integration of diverse robot policies can be streamlined from hours to minutes, revolutionizing how we deploy and evaluate robotic systems.
Trustworthiness in embodied intelligence isn't just about performance; it's about managing risk across a multi-layered framework that ensures safety and reliability in real-world applications.
Adaptive routing of perception priors allows PerceptDrive to generate optimal driving trajectories in real-time without complex post-processing.
Harness VLA boosts the performance of frozen VLA models by 38.6 percentage points on challenging manipulation tasks without the need for finetuning.
RoboDojo reveals that integrating simulation and real-world tasks can significantly enhance the evaluation of robot manipulation policies, bridging the gap between theoretical performance and practical deployment.
