Liangkai Liu — accepted AI-conference papers

2023

An Open Approach to Energy-Efficient Autonomous Mobile Robots

Liangkai Liu, Ren Zhong, Aaron Willcock, Nathan Fisher, Weisong Shi

ICRA 2023poster

Autonomous mobile robots (AMRs) have the capability to execute a wide range of tasks with minimal human intervention. However, one of the major limitations of AMRs is their limited battery life, which often results in interruptions to their task execution and the need to reach the nearest charging s…

Cited by 9 Source ↗Scholar ↗

2021

Oops! It's Too Late. Your Autonomous Driving System Needs a Faster Middleware

Tianze Wu, Baofu Wu, Sa Wang, Liangkai Liu, Shaoshan Liu, Yungang Bao +1

RA-L 2021

Autonomous Driving (AD) has entered a period of rapid development in recent years. With the amount of sensors and control logics installed increasing tremendously to guarantee robustness, a big challenge is posed for AD middleware. Both the academia and the industry are eager for an investigation of

Cited by 25 Source ↗Scholar ↗