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Cyclops enables LiDAR to produce high-quality RGB video, outperforming traditional cameras in low-light scenarios and revolutionizing robotic perception.
Current navigation agents falter in cross-context scenarios, with a significant performance drop when moving from outdoor to indoor-to-outdoor environments.
DeepCORD adapts solver parameters in real-time, outperforming traditional methods in distributed optimization across complex geometric scenarios.
Rigid body trajectory optimization can now avoid singularities and achieve faster convergence with a new structure-aware method that respects the underlying geometry.
LLMs can navigate more efficiently in unfamiliar environments by reasoning over a tree of possible paths, not just isolated waypoints, enabling them to consider en-route information gain and prune unpromising branches.
Forget pre-built maps: this new navigation agent interprets signs like a human, achieving 80% success in complex indoor environments.
Exploiting symmetry in tensegrity robot design slashes training data needs by 80% while boosting contact estimation accuracy by 15%, all with a simple graph neural network.
