Seminar: Mina Henein and Jun Zhang, ANU, 5 Dec, 4pm

When: Thurs 5th of December, 4pm

Where: Rose St Building seminar area

Speaker: Mina Henein and Jun Zhang, ANU

Title: Robust Object-aware SLAM for Dynamic Scene Understanding

Abstract: The static world assumption is standard in most simultaneous localisation and mapping (SLAM) algorithms. Increased deployment of autonomous systems to unstructured dynamic environments is driving a need to identify moving objects and estimate their velocity in real-time. Most existing SLAM based approaches rely on a database of 3D models of objects or impose significant motion constraints. In this paper, we propose a new feature-based, model-free, object-aware dynamic SLAM algorithm that exploits semantic segmentation to allow estimation of motion of rigid objects in a scene without the need to estimate the object poses or have any prior knowledge of their 3D models. The algorithm generates a map of dynamic and static structure and has the ability to extract velocities of rigid moving objects in the scene. Its performance is demonstrated on simulated, synthetic and real-world datasets.

Mina Henein: Mina is a PhD candidate at the Australian National University, and the Australian Centre of Excellence for Robotic Vision working on SLAM in dynamic environments. He is doing research under the supervision of Viorela Ila and Robert Mahony. His research interests include graph-based SLAM, dynamic SLAM and object SLAM besides kinematics and optimization techniques. Mina received his B.Sc. in Engineering and Materials Science with Honours majoring in Mechatronics from the German University in Cairo (GUC), Egypt in 2012. He then worked in the business sector for a multinational FMCG for one year as a Near-East demand manager before pursuing his masters in Advanced Robotics. He received a double M.Sc. degree; European Masters of Advanced Robotics (EMARo) from Universita degli Studi di Genova, Italy and Ecole Centrale de Nantes, France. Throughout his career, he worked as a visiting research assistant at the Italian Institute of Technology (IIT) under the supervision of Roy Featherstone and at the Autonomous Systems Lab (ASL) at ETH Zurich under the supervision of Peter Fankhauser, Marco Hutter and Roland Siegwart where he carried out his masters thesis.

Jun Zhang: Jun is a PhD student of ARC Centre of Excellence for Robotic Vision, in College of Engineering and Computer Science, Australian National University. Jun received ME and BE degrees in the School of Aeronautics of Northwestern Polytechnical University, China. During the Master’s period, Jun spent one and half year at the Institute of Computer Science and Technology, Peking University as a visiting researcher. His research interests include visual SLAM in non-static environment, scene flow estimation and multi-model fitting.

Contacts

Sydney Institute for Robotics and Intelligent Systems
info@acfr.usyd.edu.au