103 citations · 628 across the 48 of their papers we have counts for
8 papers · 1 filter
Rhythmic Representations: Learning Periodic Patterns for Scalable Place Recognition at a Sub-Linear Storage Cost
Litao Yu, Adam Jacobson, Michael Milford
Robotic and animal mapping systems share many challenges and characteristics: they must function in a wide variety of environmental conditions, enable the robot or animal to naviga…
One-Shot Reinforcement Learning for Robot Navigation with Interactive Replay
Jake Bruce, Niko Suenderhauf, Piotr Mirowski +2
Recently, model-free reinforcement learning algorithms have been shown to solve challenging problems by learning from extensive interaction with the environment. A significant issu…
Dual Quadrics from Object Detection BoundingBoxes as Landmark Representations in SLAM
Niko Sünderhauf, Michael Milford
Research in Simultaneous Localization And Mapping (SLAM) is increasingly moving towards richer world representations involving objects and high level features that enable a semanti…
Look No Further: Adapting the Localization Sensory Window to the Temporal Characteristics of the Environment
Jake Bruce, Adam Jacobson, Michael Milford
Many localization algorithms use a spatiotemporal window of sensory information in order to recognize spatial locations, and the length of this window is often a sensitive paramete…
Deja vu: Scalable Place Recognition Using Mutually Supportive Feature Frequencies
Adam Jacobson, Walter Scheirer, Michael Milford
Learning and recognition is a fundamental process performed in many robot operations such as mapping and localization. The majority of approaches share some common characteristics,…
Multi-Modal Trip Hazard Affordance Detection On Construction Sites
Sean McMahon, Niko Sünderhauf, Ben Upcroft +1
Trip hazards are a significant contributor to accidents on construction and manufacturing sites, where over a third of Australian workplace injuries occur [1]. Current safety inspe…