9 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.,…
GO: The Great Outdoors Multimodal Dataset
Peng Jiang, Kasi Viswanath, Akhil Nagariya +8
The Great Outdoors (GO) dataset is a multi-modal annotated data resource aimed at advancing ground robotics research in unstructured environments. Existing off-road datasets often…
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…
Pushing Radar Odometry Beyond the Pavement: Current Capabilities and Challenges
Shaunak Kolhe, Peng Jiang, Maggie Wigness +4
Radar offers unique advantages for localization in unstructured environments, including robustness to weather, lighting, and airborne particulates. While most prior work has studie…
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…
Learning Smooth State-Dependent Traversability from Dense Point Clouds
Zihao Dong, Alan Papalia, Leonard Jung +4
A key open challenge in off-road autonomy is that the traversability of terrain often depends on the vehicle's state. In particular, some obstacles are only traversable from some o…