1 citations · 1 across the 6 of their papers we have counts for
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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…
Real-Time Sampling-based Online Planning for Drone Interception
Gilhyun Ryou, Lukas Lao Beyer, Sertac Karaman
This paper studies high-speed online planning in dynamic environments. The problem requires finding time-optimal trajectories that conform to system dynamics, meeting computational…
Joint Localization and Planning using Diffusion
L. Lao Beyer, S. Karaman
Diffusion models have been successfully applied to robotics problems such as manipulation and vehicle path planning. In this work, we explore their application to end-to-end naviga…
NVINS: Robust Visual Inertial Navigation Fused with NeRF-augmented Camera Pose Regressor and Uncertainty Quantification
Juyeop Han, Lukas Lao Beyer, Guilherme V. Cavalheiro +1
In recent years, Neural Radiance Fields (NeRF) have emerged as a powerful tool for 3D reconstruction and novel view synthesis. However, the computational cost of NeRF rendering and…
Multi-Modal Motion Planning Using Composite Pose Graph Optimization
L. Lao Beyer, N. Balabanska, E. Tal +1
In this paper, we present a motion planning framework for multi-modal vehicle dynamics. Our proposed algorithm employs transcription of the optimization objective function, vehicle…