From the 1 of 22 linked papers with an AI index.
15 papers · 1 filter
Motion Planning in Compressed Representation Spaces
Lukas Lao Beyer, Sertac Karaman
Deep learning methods have vastly expanded the capabilities of motion planning in robotics applications, as learning priors from large-scale data has been shown to be essential in…
SCREP: Scene Coordinate Regression and Evidential Learning-based Perception-Aware Trajectory Generation
Juyeop Han, Lukas Lao Beyer, Guilherme V. Cavalheiro +1
Autonomous flight in GPS-denied indoor spaces requires trajectories that keep visual-localization error tightly bounded across varied missions. Map-based visual localization method…
UfM*: Uncertainty from Motion* for DNN Depth Estimation Using Gaussians
Soumya Sudhakar, Sertac Karaman, Vivienne Sze
Reliable uncertainty estimation is critical for deploying monocular depth deep neural networks (DNNs) in safety-critical robotic systems. Conventional uncertainty methods such as e…
Gleanmer: A 6 mW SoC for Real-Time 3D Gaussian Occupancy Mapping
Zih-Sing Fu, Peter Zhi Xuan Li, Sertac Karaman +1
High-fidelity 3D occupancy mapping is essential for many edge-based applications (such as AR/VR and autonomous navigation) but is limited by power constraints. We present Gleanmer,…
ReGen: Generative Robot Simulation via Inverse Design
Phat Nguyen, Tsun-Hsuan Wang, Zhang-Wei Hong +5
Simulation plays a key role in scaling robot learning and validating policies, but constructing simulations remains a labor-intensive process. This paper introduces ReGen, a genera…
SAFe-Copilot: Unified Shared Autonomy Framework
Phat Nguyen, Erfan Aasi, Shiva Sreeram +4
Autonomous driving systems remain brittle in rare, ambiguous, and out-of-distribution scenarios, where human driver succeed through contextual reasoning. Shared autonomy has emerge…