2 citations · 4 across the 5 of their papers we have counts for
5 papers
RUSH: Robust Contrastive Learning via Randomized Smoothing
Yijiang Pang, Boyang Liu, Jiayu Zhou
Recently, adversarial training has been incorporated in self-supervised contrastive pre-training to augment label efficiency with exciting adversarial robustness. However, the robu…
Synthesized Trust Learning from Limited Human Feedback for Human-Load-Reduced Multi-Robot Deployments
Yijiang Pang, Chao Huang, Rui Liu
Human multi-robot system (MRS) collaboration is demonstrating potentials in wide application scenarios due to the integration of human cognitive skills and a robot team's powerful…
Trust Aware Emergency Response for A Resilient Human-Swarm Cooperative System
Yijiang Pang, Rui Liu
A human-swarm cooperative system, which mixes multiple robots and a human supervisor to form a heterogeneous team, is widely used for emergent scenarios such as criminal tracking i…
Trust Repairing for Human-Swarm Cooperation inDynamic Task Response
Yijiang Pang, Rui Liu
Emergency happens in human-UAV cooperation, such as criminal activity tracking and urgent needs for ground assistance. Emergency response usually has high requirements on the motio…
Proficiency Constrained Multi-Agent Reinforcement Learning for Environment-Adaptive Multi UAV-UGV Teaming
Qifei Yu, Zhexin Shen, Yijiang Pang +1
A mixed aerial and ground robot team, which includes both unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs), is widely used for disaster rescue, social security,…