Ye Chengcong

HKU Astar is a student interest group focused on research and development in the combination of Robotics and AI algorithms. It collaborates with HKU RoboMaster in RoboMaster university competition series hosted by DJI, responsible for the mechanical and embedded systems design of some robots and the development of vision, localization, navigation, and decision-making systems applied to the fully automatic sentry robot and the Radar. Starting from next semester, the team will participate individually in other AI-related competitions, such as the Intelligent UAV Championship currently held by DJI. For the UAV Championship, the team will work on the localization, navigation, and motion planning of a drone to make it fly swiftly and smoothly through objective rings, as well as avoid stationary or moving obstacles in a complicated environment.

Robomaster is a national robotics competition for university students, hosted by DJI. The project is about forming a team to design various types of smart robots which can engage in face-to-face, videogame-style battles. The preparation process involves the knowledge in the following disciplines: mechanical and hardware design, control theory application, computer vision and smart algorithm, technical management. The ultimate purpose of the project is to develop the skills, quality and team spirit of engineering students that can be beneficial in their future career.

AI-Driving is an interdisciplinary endeavor in experiential learning, in which students apply technical knowledges in A.I. and robotics. In this project, students will learn knowledge about computer vision, artificial intelligence and robotics and implement AI algorithms to work on auto-driving vehicles running in a real miniature environment. The objective of the project is to allow students to gain insights about the development framework for autonomous vehicles, and to attempt problem such as lane following and object recognition. Students will also form a team representing HKU to participate in International competitions such as AI-Driving Olympics held by the DuckieTown Foundation and other contests related to AI-Driving, e.g., AWS DeepRacer.

This project aims to develop the set of technologies to achieve convenient-to-use mobility support for daily use of the elderly. In this project, we are developing a smart elderly walker which is intended to play an active role in an elderly person’s daily life, with three fundamental functionalities that do not exist or not well supported by (smart) walkers in the market: smart walking assistance; falling prevention and support; autonomous mobility.
A set of mechanical, control, sensory, and AI technologies is being developed including:
(1) novel walker mechanical structure with omnidirectional mobility and outrigger mechanisms;
(2) dual-mode actuation and control for walking/standing support and fall prevention/ recovery;
(3) multimodal sensory data collection through soft sensory skin, and data processing on device and in the cloud, for event detection and control such as user front following and fall detection;
(4) sound-source localization for elderly localisation and auto-navigation of walker.