6 papers
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.,…
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…
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…
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…
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…
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…