Lan Wu

Lan Wu

Perception, Mapping, SLAM

About me

I am a postdoctoral research fellow from the Robotics Institute, School of Mechanical and Mechatronic Engineering, University of Technology Sydney. My principal supervisor is A/Prof. Teresa Vidal-Calleja and co-supervisor is Dr. Alen Alempijevic. My thesis is entitled “Probabilistic Implicit Surfaces for Localisation, Mapping and Planning”. My research focus is on probabilistic perception with depth sensors to perform efficient and effective mapping, accurate localisation and optimisation-based path planning for robotic systems.

I’m thrilled to announce that the program committee has decided to accept me as a member of the 30-strong cohort of the RSS Pioneers Workshop 2024.
Looking forward to seeing you all in Delft, Netherlands, July 2024!

Selected key research outcomes (2020-2024)

  • IDMP - Interactive Distance Field Mapping and Planning to Enable Human-Robot Collaboration
    Under view of IEEE Robotics and Automation Letters 2024
    Usama Ali*, Lan Wu*, Adrian Muller, Fouad Sukkar, Tobias Kaupp and Teresa Vidal-Calleja
    * These authors are co-first authors and contributed equally to this work.
    Please find our paper and code here: paper and code.

  • Log-GPIS-MOP: A Unified Representation for Mapping, Odometry and Planning
    IEEE Transactions on Robotics, vol. 39, pp. 4078-4094, October 2023
    Lan Wu, Ki Myung Brian Lee, Cedric Le Gentil and Teresa Vidal-Calleja
    Please find our paper here: paper and video

  • Faithful Euclidean Distance Field from Log-Gaussian Process Implicit Surfaces
    IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 2461–2468, 2021
    Lan Wu, Ki Myung Brian Lee, Liyang Liu and Teresa Vidal-Calleja
    Please find our paper and video.

  • Skeleton-Based Conditionally Independent Gaussian Process Implicit Surfaces for Fusion in Sparse to Dense 3D Reconstruction
    IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1532–1539, 2020
    Lan Wu, Raphael Falque, Victor Perez-Puchalt, Liyang Liu, Nico Pietroni and Teresa Vidal-Calleja
    Please find our paper and video.

Selected robotic projects (2020-2022)

  • Surface Reconstruction for the Meat and Livestock Project
    I applied my research outcomes in the meat and livestock project for trait estimation, funded by the Australian Government Department of Agriculture&Water Resources as part of its Rural R&D for Profit programme, Meat and Livestock Australia under the Grant V.RDP.2005. By using the probabilistic mapping approaches developed during my PhD, my main objective was to convert and process noisy and incomplete point clouds and depth images of non-rigid livestock and rigid carcass into 3D meshes for further processing.

  • Multi-sensor Perception, Calibration and Synchronisation for a Fast Off-road Vehicle
    I also contributed to UTS’ next generation of fast-wheeled robots. During my studies, UTS built FORV, a Fast Off-Road Vehicle for Defence Applications and I was responsible for establishing the multi-sensor fusion platform for mapping and navigation. Calibrating and working across several visual sensors including a binocular camera, a 3D LiDAR and an inertial measurement unit, we managed to have a data collection and synchronisation system based on NVIDIA Jetson and ROS.

  • Simultaneous Localisation and Mapping for Locomotive No.1
    I had a precious opportunity to work with my colleagues to reconstruct the digital representation of the historical train Locomotive No. 1 in the Powerhouse Museum. The datasets were collected by LiDAR sensor and RGB-D camera along with an IMU sensor. We operated the sensors around the train to have high-quality observations and then utilise various SLAM frameworks to produce an accurate surface of the train. Moreover, I generated the colored point cloud of the full train using RGB information for LiDAR measurements.

Contact

Please contact me:
iriswu076@gmail.com