Shibo Zhao - IEEE Xplore Author Profile
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Shibo Zhao

Publications
11
Citations
277
Publications by Year
20172024
Co-Authors:
Show All Co-Authors (130)
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Shibo Zhao

Affiliation

Carnegie Mellon University

Publication Topics

Biography

Shibo Zhao (Student Member, IEEE) is currently working toward the Ph.D. degree with Robotics Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.,He is currently a CMU Explorer Team and a SLAM Researcher. His research interests include SLAM and 3-D reconstruction in challenging environments.(Based on document published on 16 October 2023).
Publications
11
Citations
277
Publications by Year
20172024
Co-Authors:
Show All Co-Authors (130)
Author's Published Works

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SubT-MRS Dataset: Pushing SLAM Towards All-weather Environments

Shibo Zhao;Yuanjun Gao;Tianhao Wu;Damanpreet Singh;Rushan Jiang;Haoxiang Sun;Mansi Sarawata;Yuheng Qiu;Warren Whittaker;Ian Higgins;Yi Du;Shaoshu Su;Can Xu;John Keller;Jay Karhade;Lucas Nogueira;Sourojit Saha;Ji Zhang;Wenshan Wang;Chen Wang;Sebastian Scherer

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2024 | Conference Paper |
Cited by: Papers (9)
Simultaneous localization and mapping (SLAM) is a fundamental task for numerous applications such as autonomous navigation and exploration. Despite many SLAM datasets have been released, current SLAM solutions still struggle to have sustained and resilient performance. One major issue is the absence of high-quality datasets including diverse all-weather conditions and a reliable metric for assessi...Show More

SubT-MRS Dataset: Pushing SLAM Towards All-weather Environments

Shibo Zhao;Yuanjun Gao;Tianhao Wu;Damanpreet Singh;Rushan Jiang;Haoxiang Sun;Mansi Sarawata;Yuheng Qiu;Warren Whittaker;Ian Higgins;Yi Du;Shaoshu Su;Can Xu;John Keller;Jay Karhade;Lucas Nogueira;Sourojit Saha;Ji Zhang;Wenshan Wang;Chen Wang;Sebastian Scherer

Year: 2024 | Conference Paper |

Present and Future of SLAM in Extreme Environments: The DARPA SubT Challenge

Kamak Ebadi;Lukas Bernreiter;Harel Biggie;Gavin Catt;Yun Chang;Arghya Chatterjee;Christopher E. Denniston;Simon-Pierre Deschênes;Kyle Harlow;Shehryar Khattak;Lucas Nogueira;Matteo Palieri;Pavel Petráček;Matěj Petrlík;Andrzej Reinke;Vít Krátký;Shibo Zhao;Ali-akbar Agha-mohammadi;Kostas Alexis;Christoffer Heckman;Kasra Khosoussi;Navinda Kottege;Benjamin Morrell;Marco Hutter;Fred Pauling;François Pomerleau;Martin Saska;Sebastian Scherer;Roland Siegwart;Jason L. Williams;Luca Carlone

IEEE Transactions on Robotics
Year: 2024 | Volume: 40 | Journal Article |
Cited by: Papers (39)
This article surveys recent progress and discusses future opportunities for simultaneous localization and mapping (SLAM) in extreme underground environments. SLAM in subterranean environments, from tunnels, caves, and man-made underground structures on Earth, to lava tubes on Mars, is a key enabler for a range of applications, such as planetary exploration, search and rescue, disaster response, an...Show More

Present and Future of SLAM in Extreme Environments: The DARPA SubT Challenge

Kamak Ebadi;Lukas Bernreiter;Harel Biggie;Gavin Catt;Yun Chang;Arghya Chatterjee;Christopher E. Denniston;Simon-Pierre Deschênes;Kyle Harlow;Shehryar Khattak;Lucas Nogueira;Matteo Palieri;Pavel Petráček;Matěj Petrlík;Andrzej Reinke;Vít Krátký;Shibo Zhao;Ali-akbar Agha-mohammadi;Kostas Alexis;Christoffer Heckman;Kasra Khosoussi;Navinda Kottege;Benjamin Morrell;Marco Hutter;Fred Pauling;François Pomerleau;Martin Saska;Sebastian Scherer;Roland Siegwart;Jason L. Williams;Luca Carlone

Year: 2024 | Volume: 40 | Journal Article |

Exploring the Most Sectors at the DARPA Subterranean Challenge Finals

Chao Cao;Lucas Nogueira;Hongbiao Zhu;John Keller;Graeme Best;Rohit Garg;David Kohanbash;Jay Maier;Shibo Zhao;Fan Yang;Katarina Cujic;Ryan Darnley;Robert DeBortoli;Bill Drozd;Peigen Sun;Ian Higgins;Steven Willits;Greg Armstrong;Ji Zhang;Geoffrey A. Hollinger;Matthew Travers;Sebastian Scherer

Field Robotics
Year: 2023 | Volume: 3 | Journal Article |
Autonomous robot navigation in austere environments is critical to missions like “search and rescue”, yet it remains difficult to achieve. The recent DARPA Subterranean Challenge (SubT) highlights prominent challenges including GPS-denied navigation through rough terrains, rapid exploration in large-scale three-dimensional (3D) space, and interrobot coordination over unreliable communication. Solv...Show More

Exploring the Most Sectors at the DARPA Subterranean Challenge Finals

Chao Cao;Lucas Nogueira;Hongbiao Zhu;John Keller;Graeme Best;Rohit Garg;David Kohanbash;Jay Maier;Shibo Zhao;Fan Yang;Katarina Cujic;Ryan Darnley;Robert DeBortoli;Bill Drozd;Peigen Sun;Ian Higgins;Steven Willits;Greg Armstrong;Ji Zhang;Geoffrey A. Hollinger;Matthew Travers;Sebastian Scherer

Year: 2023 | Volume: 3 | Journal Article |

PyPose: A Library for Robot Learning with Physics-based Optimization

Chen Wang;Dasong Gao;Kuan Xu;Junyi Geng;Yaoyu Hu;Yuheng Qiu;Bowen Li;Fan Yang;Brady Moon;Abhinav Pandey;Aryan;Jiahe Xu;Tianhao Wu;Haonan He;Daning Huang;Zhongqiang Ren;Shibo Zhao;Taimeng Fu;Pranay Reddy;Xiao Lin;Wenshan Wang;Jingnan Shi;Rajat Talak;Kun Cao;Yi Du;Han Wang;Huai Yu;Shanzhao Wang;Siyu Chen;Ananth Kashyap;Rohan Bandaru;Karthik Dantu;Jiajun Wu;Lihua Xie;Luca Carlone;Marco Hutter;Sebastian Scherer

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2023 | Conference Paper |
Cited by: Papers (16)
Deep learning has had remarkable success in robotic perception, but its data-centric nature suffers when it comes to generalizing to ever-changing environments. By contrast, physics-based optimization generalizes better, but it does not perform as well in complicated tasks due to the lack of high-level semantic information and reliance on manual parametric tuning. To take advantage of these two co...Show More

PyPose: A Library for Robot Learning with Physics-based Optimization

Chen Wang;Dasong Gao;Kuan Xu;Junyi Geng;Yaoyu Hu;Yuheng Qiu;Bowen Li;Fan Yang;Brady Moon;Abhinav Pandey;Aryan;Jiahe Xu;Tianhao Wu;Haonan He;Daning Huang;Zhongqiang Ren;Shibo Zhao;Taimeng Fu;Pranay Reddy;Xiao Lin;Wenshan Wang;Jingnan Shi;Rajat Talak;Kun Cao;Yi Du;Han Wang;Huai Yu;Shanzhao Wang;Siyu Chen;Ananth Kashyap;Rohan Bandaru;Karthik Dantu;Jiajun Wu;Lihua Xie;Luca Carlone;Marco Hutter;Sebastian Scherer

Year: 2023 | Conference Paper |

Resilient and Modular Subterranean Exploration with a Team of Roving and Flying Robots

Sebastian Scherer;Vasu Agrawal;Graeme Best;Chao Cao;Katarina Cujic;Ryan Darnley;Robert DeBortoli;Eric Dexheimer;Bill Drozd;Rohit Garg;Ian Higgins;John Keller;David Kohanbash;Lucas Nogueira;Roshan Pradhan;Michael Tatum;Vaibhav K. Viswanathan;Steven Willits;Shibo Zhao;Hongbiao Zhu;Dan Abad;Tim Angert;Greg Armstrong;Ralph Boirum;Adwait Dongare;Matthew Dworman;Shengjie Hu;Joshua Jaekel;Ran Ji;Alice Lai;Yu Hsuan Lee;Anh Luong;Joshua Mangelson;Jay Maier;James Picard;Kevin Pluckter;Andrew Saba;Manish Saroya;Emily Scheide;Nathaniel Shoemaker-Trejo;Joshua Spisak;Jim Teza;Fan Yang;Andrew Wilson;Henry Zhang;Howie Choset;Michael Kaess;Anthony Rowe;Sanjiv Singh;Ji Zhang;Geoffrey A. Hollinger;Matthew Travers

Field Robotics
Year: 2022 | Volume: 2 | Journal Article |
Subterranean robot exploration is difficult, with many mobility, communications, and navigation challenges that require an approach with a diverse set of systems, and reliable autonomy. While prior work has demonstrated partial successes in addressing the problem, here we convey a comprehensive approach to address the problem of subterranean exploration in a wide range of tunnel, urban, and cave e...Show More

Resilient and Modular Subterranean Exploration with a Team of Roving and Flying Robots

Sebastian Scherer;Vasu Agrawal;Graeme Best;Chao Cao;Katarina Cujic;Ryan Darnley;Robert DeBortoli;Eric Dexheimer;Bill Drozd;Rohit Garg;Ian Higgins;John Keller;David Kohanbash;Lucas Nogueira;Roshan Pradhan;Michael Tatum;Vaibhav K. Viswanathan;Steven Willits;Shibo Zhao;Hongbiao Zhu;Dan Abad;Tim Angert;Greg Armstrong;Ralph Boirum;Adwait Dongare;Matthew Dworman;Shengjie Hu;Joshua Jaekel;Ran Ji;Alice Lai;Yu Hsuan Lee;Anh Luong;Joshua Mangelson;Jay Maier;James Picard;Kevin Pluckter;Andrew Saba;Manish Saroya;Emily Scheide;Nathaniel Shoemaker-Trejo;Joshua Spisak;Jim Teza;Fan Yang;Andrew Wilson;Henry Zhang;Howie Choset;Michael Kaess;Anthony Rowe;Sanjiv Singh;Ji Zhang;Geoffrey A. Hollinger;Matthew Travers

Year: 2022 | Volume: 2 | Journal Article |

Super Odometry: IMU-centric LiDAR-Visual-Inertial Estimator for Challenging Environments

Shibo Zhao;Hengrui Zhang;Peng Wang;Lucas Nogueira;Sebastian Scherer

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2021 | Conference Paper |
Cited by: Papers (101)
We propose Super Odometry, a high-precision multi-modal sensor fusion framework, providing a simple but effective way to fuse multiple sensors such as LiDAR, camera, and IMU sensors and achieve robust state estimation in perceptually-degraded environments. Different from traditional sensor-fusion methods, Super Odometry employs an IMU-centric data processing pipeline, which combines the advantages...Show More

Super Odometry: IMU-centric LiDAR-Visual-Inertial Estimator for Challenging Environments

Shibo Zhao;Hengrui Zhang;Peng Wang;Lucas Nogueira;Sebastian Scherer

Year: 2021 | Conference Paper |

Vanishing Point Aided LiDAR-Visual-Inertial Estimator

Peng Wang;Zheng Fang;Shibo Zhao;Yongnan Chen;Ming Zhou;Shan An

2021 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2021 | Conference Paper |
Cited by: Papers (9)
In this paper, we propose a vanishing point aided LiDAR-Visual-Inertial estimator to achieve real-time, low-drift and robust pose estimation. The proposed method is mainly composed of 3 sequential modules, namely IMU-aided vanishing point (VP) detection module, voxel-map based feature depth association module, and visual inertial fixed-lag smoother module. The IMU-aided VP detection module will de...Show More

Vanishing Point Aided LiDAR-Visual-Inertial Estimator

Peng Wang;Zheng Fang;Shibo Zhao;Yongnan Chen;Ming Zhou;Shan An

Year: 2021 | Conference Paper |

TP-TIO: A Robust Thermal-Inertial Odometry with Deep ThermalPoint

Shibo Zhao;Peng Wang;Hengrui Zhang;Zheng Fang;Sebastian Scherer

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2020 | Conference Paper |
Cited by: Papers (37)
To achieve robust motion estimation in visually degraded environments, thermal odometry has been an attraction in the robotics community. However, most thermal odometry methods are purely based on classical feature extractors, which is difficult to establish robust correspondences in successive frames due to sudden photometric changes and large thermal noise. To solve this problem, we propose Ther...Show More

TP-TIO: A Robust Thermal-Inertial Odometry with Deep ThermalPoint

Shibo Zhao;Peng Wang;Hengrui Zhang;Zheng Fang;Sebastian Scherer

Year: 2020 | Conference Paper |

A Robust Laser-Inertial Odometry and Mapping Method for Large-Scale Highway Environments

Shibo Zhao;Zheng Fang;HaoLai Li;Sebastian Scherer

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2019 | Conference Paper |
Cited by: Papers (59)
In this paper, we propose a novel laser-inertial odometry and mapping method to achieve real-time, low-drift and robust pose estimation in large-scale highway environments. The proposed method is mainly composed of four sequential modules, namely scan pre-processing module, dynamic object detection module, laser-inertial odometry module and laser mapping module. Scan pre-processing module uses ine...Show More

A Robust Laser-Inertial Odometry and Mapping Method for Large-Scale Highway Environments

Shibo Zhao;Zheng Fang;HaoLai Li;Sebastian Scherer

Year: 2019 | Conference Paper |

A Real-time and Low-cost 3D SLAM System Based on a Continuously Rotating 2D Laser Scanner

Zheng Fang;Shibo Zhao;Shiguang Wen

2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER)
Year: 2017 | Conference Paper |
Cited by: Papers (4)
This paper presents a real-time and low-cost 3D SLAM system which is suitable for autonomous navigation and large scale environment reconstruction. The 3D SLAM system is based on a rotating 2D planar laser scanner driven by a step motor. The challenge is that the range measurements are received at different times when the 3D Lidar is moving, which will result in big distortion of the local 3D poin...Show More

A Real-time and Low-cost 3D SLAM System Based on a Continuously Rotating 2D Laser Scanner

Zheng Fang;Shibo Zhao;Shiguang Wen

Year: 2017 | Conference Paper |

A Real-time Handheld 3D Temperature Field Reconstruction System

Shibo Zhao;Zheng Fang;Shiguang Wen

2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER)
Year: 2017 | Conference Paper |
Cited by: Papers (3)
This paper presents a real-time and handheld 3D temperature field SLAM system which is not only useful in search and rescue robots, but also in building energy auditing, and fault diagnose of critical equipments in factories. The 3D temperature field SLAM system is built on a thermal camera and an RGB-D camera. The problem is how to fuse the temperature information with the RGB information to esti...Show More

A Real-time Handheld 3D Temperature Field Reconstruction System

Shibo Zhao;Zheng Fang;Shiguang Wen

Year: 2017 | Conference Paper |

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