32 citations · 131 across the 10 of their papers we have counts for
8 papers · 1 filter
Exploiting Natural Language for Efficient Risk-Aware Multi-robot SaR Planning
Vikram Shree, Beatriz Asfora, Rachel Zheng +3
The ability to develop a high-level understanding of a scene, such as perceiving danger levels, can prove valuable in planning multi-robot search and rescue (SaR) missions. In this…
Detecting and Mapping Trees in Unstructured Environments with a Stereo Camera and Pseudo-Lidar
Brian H. Wang, Carlos Diaz-Ruiz, Jacopo Banfi +1
We present a method for detecting and mapping trees in noisy stereo camera point clouds, using a learned 3-D object detector. Inspired by recent advancements in 3-D object detectio…
Planning Paths Through Unknown Space by Imagining What Lies Therein
Yutao Han, Jacopo Banfi, Mark Campbell
This paper presents a novel framework for planning paths in maps containing unknown spaces, such as from occlusions. Our approach takes as input a semantically-annotated point clou…
Mixed-Integer Linear Programming Models for Multi-Robot Non-Adversarial Search
Beatriz A. Asfora, Jacopo Banfi, Mark Campbell
In this letter, we consider the Multi-Robot Efficient Search Path Planning (MESPP) problem, where a team of robots is deployed in a graph-represented environment to capture a movin…
DeepSemanticHPPC: Hypothesis-based Planning over Uncertain Semantic Point Clouds
Yutao Han, Hubert Lin, Jacopo Banfi +2
Planning in unstructured environments is challenging -- it relies on sensing, perception, scene reconstruction, and reasoning about various uncertainties. We propose DeepSemanticHP…
Pedestrian Motion Model Using Non-Parametric Trajectory Clustering and Discrete Transition Points
Yutao Han, Rina Tse, Mark Campbell
This paper presents a pedestrian motion model that includes both low level trajectory patterns, and high level discrete transitions. The inclusion of both levels creates a more gen…