142 citations · 712 across the 76 of their papers we have counts for
3 papers · 2 filters
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…
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,…