Abstract Knowledge about the own pose is key for all mobile robot applications. Thus pose
estimation is part of the core functionalities of mobile robots. Over the last two decades …

Knowledge about the own pose is key for all mobile robot applications. Thus pose
estimation is part of the core functionalities of mobile robots. In the last two decades, LiDAR …

Brain-inspired computing (BIC) is an emerging research field that aims to build fundamental
theories, models, hardware architectures, and application systems toward more general …

Neural Radiance Fields (NeRF) have emerged as a powerful paradigm for 3D scene
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …

This letter proposes LONER, the first real-time LiDAR SLAM algorithm that uses a neural
implicit scene representation. Existing implicit mapping methods for LiDAR show promising …

We introduce the UT Campus Object Dataset (CODa), a mobile robot egocentric perception
dataset collected on the University of Texas Austin Campus. Our dataset contains 8.5 hours …

We introduce an integrated precise LiDAR, Inertial, and Visual (LIV) multimodal sensor
fused mapping system that builds on the differentiable Gaussians to improve the mapping …

Leveraging multiple sensors enhances complex environmental perception and increases
resilience to varying luminance conditions and high-speed motion patterns, achieving …

This paper presents a comprehensive forest mapping system using a customized drone
payload equipped with Light Detection and Ranging (LiDAR), cameras, a Global Navigation …

Terrain-aware perception holds the potential to improve the robustness and accuracy of
autonomous robot navigation in the wilds, thereby facilitating effective off-road traversals …