6 papers
Balancing Act: Trading Off Odometry and Map Registration for Efficient Lidar Localization
Katya M. Papais, Daniil Lisus, Cedric Le Gentil +2
Most autonomous vehicles rely on accurate and efficient localization, which is achieved by comparing live sensor data to a preexisting map, to navigate their environment. Balancing…
Integral Forms in Matrix Lie Groups
Timothy D Barfoot
Matrix Lie groups provide a language for describing motion in such fields as robotics, computer vision, and graphics. When using these tools, we are often faced with turning infini…
A New Wave in Robotics: Survey on Recent mmWave Radar Applications in Robotics
Kyle Harlow, Hyesu Jang, Timothy D. Barfoot +2
We survey the current state of millimeterwave (mmWave) radar applications in robotics with a focus on unique capabilities, and discuss future opportunities based on the state of th…
Safe and Smooth: Certified Continuous-Time Range-Only Localization
Frederike Dümbgen, Connor Holmes, Timothy D. Barfoot
A common approach to localize a mobile robot is by measuring distances to points of known positions, called anchors. Locating a device from distance measurements is typically posed…
Field Testing of a Stochastic Planner for ASV Navigation Using Satellite Images
Philip Huang, Tony Wang, Florian Shkurti +1
We introduce a multi-sensor navigation system for autonomous surface vessels (ASV) intended for water-quality monitoring in freshwater lakes. Our mission planner uses satellite ima…
FoMo: A Proposal for a Multi-Season Dataset for Robot Navigation in Forêt Montmorency
MatÄj Boxan, Alexander Krawciw, Effie Daum +4
In this paper, we propose the FoMo (Forêt Montmorency) dataset: a comprehensive, multi-season data collection. Located in the Montmorency Forest, Quebec, Canada, our dataset will…