activity
20242026
most citedLiDAR Inertial Odometry And Mapping Using Learned Registration-Relevant Features

1 citations · 1 across the 7 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Online Geometric Change Detection via Scene Decomposition

David Thorne, Samuel Jia Cong Chua, Nakul Joshi +4

Autonomous robots are increasingly deployed on long duration single- and multi-session missions in dynamic environments, where the ability to identify environmental changes such as…

cs.RO2026

PinNet: Keypoint-Aware Learned Local Descriptors with Geometric Embedding for Loop Closure in LiDAR SLAM

Yanlong Ma, Nakul S. Joshi, Christa S. Robison +2

Loop closure is essential to reduce drift and build globally consistent maps in large-scale environments. However, reliable loop closure with only geometric information from, e.g.,…

cs.RO2025

Geometric Multi-Session Map Merging with Learned Local Descriptors

Yanlong Ma, Nakul S. Joshi, Christa S. Robison +2

Multi-session map merging is crucial for extended autonomous operations in large-scale environments. In this paper, we present GMLD, a learning-based local descriptor framework for…

cs.RO2025

OptMap: Geometric Map Distillation via Submodular Maximization

David Thorne, Nathan Chan, Christa S. Robison +2

Autonomous robots rely on geometric maps to inform a diverse set of perception and decision-making algorithms. As autonomy requires reasoning and planning on multiple scales, each…

cs.RO2024

Quaternion Sliding Variables in Manipulator Control

Brett T. Lopez, Jean-Jacques Slotine

We present two quaternion-based sliding variables for controlling the orientation of a manipulator's end-effector. Both sliding variables are free of singularities and represent gl…

eess.SY2024

Information Control Barrier Functions: Preventing Localization Failures in Mobile Systems Through Control

Samuel G. Gessow, David Thorne, Brett T. Lopez

This paper develops a new framework for preventing localization failures in mobile systems that must estimate their state using measurements. Safety is guaranteed by imposing the n…

cs.RO2024★ 1 cited

LiDAR Inertial Odometry And Mapping Using Learned Registration-Relevant Features

Zihao Dong, Jeff Pflueger, Leonard Jung +5

SLAM is an important capability for many autonomous systems, and modern LiDAR-based methods offer promising performance. However, for long duration missions, existing works that ei…

cs.RO2024

Submodular Optimization for Keyframe Selection & Usage in SLAM

David Thorne, Nathan Chan, Yanlong Ma +3

Keyframes are LiDAR scans saved for future reference in Simultaneous Localization And Mapping (SLAM), but despite their central importance most algorithms leave choices of which sc…