Real Time
Real-time processing focuses on developing systems capable of analyzing and responding to data instantaneously, crucial for applications demanding immediate feedback. Current research emphasizes efficient algorithms and model architectures, such as those based on deep learning, to reduce computational latency in diverse domains including robotics, healthcare, and AI-assisted tutoring. This field's advancements are driving progress in areas like autonomous navigation, personalized healthcare monitoring, and human-computer interaction, enabling more responsive and effective systems.
Papers
Safe and Real-Time Consistent Planning for Autonomous Vehicles in Partially Observed Environments via Parallel Consensus Optimization
Lei Zheng, Rui Yang, Minzhe Zheng, Michael Yu Wang, Jun Ma
Real-time Coupled Centroidal Motion and Footstep Planning for Biped Robots
Tara Bartlett, Ian R. Manchester
Towards Real-Time Generation of Delay-Compensated Video Feeds for Outdoor Mobile Robot Teleoperation
Neeloy Chakraborty, Yixiao Fang, Andre Schreiber, Tianchen Ji, Zhe Huang, Aganze Mihigo, Cassidy Wall, Abdulrahman Almana, Katherine Driggs-Campbell