TY - GEN
T1 - Online 3D Frontier-Based UGV and UAV Exploration Using Direct Point Cloud Visibility
AU - Williams, Jason
AU - Jiang, Shu
AU - O'brien, Matthew
AU - Wagner, Glenn
AU - Hernandez, Emili
AU - Cox, Mark
AU - Pitt, Alex
AU - Arkin, Ron
AU - Hudson, Nicolas
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/14
Y1 - 2020/9/14
N2 - While robots have long been proposed as a tool to reduce human personnel's exposure to danger in subterranean environments, these environments also present significant challenges to the development of these robots. Fundamental to this challenge is the problem of autonomous exploration. Frontier-based methods have been a powerful and successful approach to exploration, but complex 3D environments remain a challenge when online employment is required. This paper presents a new approach that addresses the complexity of operating in 3D by directly modelling the boundary between observed free and unobserved space (the frontier), rather than utilising dense 3D volumetric representations. By avoiding a representation involving a single map, it also achieves scalability to problems where Simultaneous Localisation and Matching (SLAM) loop closures are essential. The approach enabled a team of seven ground and air robots to autonomously explore the DARPA Subterranean Challenge Urban Circuit, jointly traversing over 8 km in a complex and communication denied environment.
AB - While robots have long been proposed as a tool to reduce human personnel's exposure to danger in subterranean environments, these environments also present significant challenges to the development of these robots. Fundamental to this challenge is the problem of autonomous exploration. Frontier-based methods have been a powerful and successful approach to exploration, but complex 3D environments remain a challenge when online employment is required. This paper presents a new approach that addresses the complexity of operating in 3D by directly modelling the boundary between observed free and unobserved space (the frontier), rather than utilising dense 3D volumetric representations. By avoiding a representation involving a single map, it also achieves scalability to problems where Simultaneous Localisation and Matching (SLAM) loop closures are essential. The approach enabled a team of seven ground and air robots to autonomously explore the DARPA Subterranean Challenge Urban Circuit, jointly traversing over 8 km in a complex and communication denied environment.
UR - http://www.scopus.com/inward/record.url?scp=85096146217&partnerID=8YFLogxK
U2 - 10.1109/MFI49285.2020.9235268
DO - 10.1109/MFI49285.2020.9235268
M3 - Conference contribution
AN - SCOPUS:85096146217
T3 - IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
SP - 263
EP - 270
BT - 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020
Y2 - 14 September 2020 through 16 September 2020
ER -