7 papers
SCOPE: Field-of-View-Aware Path Planning in Unknown 3D Environments via Safety-Volume Certification
Junbin Yuan, Muqing Cao, Yunwoo Lee +2
Safe navigation with a body-mounted limited-field-of-view sensor requires the complete robot-inflated volume of an intended motion to be observed and verified free before execution…
PRoID: Predicted Rate of Information Delivery in Multi-Robot Exploration and Relaying
Seungchan Kim, Seungjae Baek, Micah Corah +3
We address Multi-Robot Exploration and Relaying (MRER): a team of robots must explore an unknown environment and deliver acquired information to a fixed base station within a missi…
Hierarchical Planning for Long-Horizon Multi-Target Tracking Under Target Motion Uncertainty
Junbin Yuan, Brady Moon, Muqing Cao +1
Achieving persistent tracking of multiple dynamic targets over a large spatial area poses significant challenges for a single-robot system with constrained sensing capabilities. As…
MapExRL: Human-Inspired Indoor Exploration with Predicted Environment Context and Reinforcement Learning
Narek Harutyunyan, Brady Moon, Seungchan Kim +3
Path planning for robotic exploration is challenging, requiring reasoning over unknown spaces and anticipating future observations. Efficient exploration requires selecting budget-…
PIPE Planner: Pathwise Information Gain with Map Predictions for Indoor Robot Exploration
Seungjae Baek, Brady Moon, Seungchan Kim +4
Autonomous exploration in unknown environments requires estimating the information gain of an action to guide planning decisions. While prior approaches often compute information g…
MapEx: Indoor Structure Exploration with Probabilistic Information Gain from Global Map Predictions
Cherie Ho, Seungchan Kim, Brady Moon +6
Exploration is a critical challenge in robotics, centered on understanding unknown environments. In this work, we focus on robots exploring structured indoor environments which are…