Seminars & Colloquiums

SEMINAR

ARC Seminar: Object tracking for robot dynamic perception

Speaker(s) Shen Lyuyu
Date & Time 23 July, 2021 @ 5:00 pm to 6:00 pm
Venue Online

    Title: Object tracking for robot dynamic perception   Abstract: Object tracking, trying to find the series locations of interested objects in time consecutively sensor input frames, is widely applied to various robot systems like autonomous driving as an important dynamic perception function. According to different number of objects, object tracking can be defined […]

COLLOQUIUM

IAS-16 x Lattel Robotics: AI Application Workshop

Speaker(s) Dr. Jeffrey Tan
Date & Time 22 June, 2021 @ 10:00 am to 6:00 pm
Venue E4-04-05

In conjunction with the 16th International Conference on Intelligent Autonomous Systems, ARC is excited to host a workshop on AI Applications for robotics.   Taught by Dr. Jeffrey Tan of Lattel Robotics, participants will gain insights on technical service robot development with autonomous systems. Participants will each be provided, by loan/sale, with Jupiter IO, an […]

SEMINAR

Zoom with ARC

Speaker(s) Prof. Marcelo Ang and other engineers working on projects in ARC
Date & Time 17 April, 2020 @ 2:00 pm to 4:00 pm
Venue Zoom: https://nus-sg.zoom.us/meeting/register/upwrdeCsqTsqJqI5JdWmicrbTcdYGOgjxg

COLLOQUIUM

RobotX Interactive Forum

Date & Time 4 December, 2019
Venue Suntec City

In collaboration with the Future Systems and Technology Directorate (FSTD), US Office of Naval Research (ONR) and Robonation,  NUS Advanced Robotics Centre (ARC) is proud to be part of the successful 2019 RobotX Interactive Forum from 4 to 6 December 2019 at Suntec Singapore. Over 150 delegates, including students, academia, government and industry delegates attended […]

SEMINAR

Deep Learning for Perception in Autonomous Vehicles

Speaker(s) Holger Caesar
Date & Time 8 May, 2019
Venue NUS Faculty of Engineering, Lecture Theater 1 (LT1)

Autonomous vehicles are a breakthrough technology expected to make our lives safer and more comfortable. Data-driven deep learning approaches are essential to perceive the real world. Current datasets lack in complexity and size to train such methods. Therefore we present the nuScenes dataset – the largest existing multimodal dataset for autonomous driving. The goal of […]

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