54 citations · 160 across the 26 of their papers we have counts for
26 papers
ForceRFT: Refining VLA Actions through Force-Guided Residual Reinforcement Learning
Yichen Wang, Chaoyang Zhang, Xuqi Su +3
Force-conditioned vision-language-action (VLA) policies can respond to contact, but when trained solely on demonstrations, their recovery behavior may be limited by demonstration c…
Parallel Optimization with Hard Safety Constraints for Cooperative Planning of Connected Autonomous Vehicles
Zhenmin Huang, Haichao Liu, Shaojie Shen +1
The development of connected autonomous vehicles (CAVs) facilitates the enhancement of traffic efficiency in complicated scenarios. In unsignalized roundabout scenarios, difficulti…
Decentralized iLQR for Cooperative Trajectory Planning of Connected Autonomous Vehicles via Dual Consensus ADMM
Zhenmin Huang, Shaojie Shen, Jun Ma
Developments in cooperative trajectory planning of connected autonomous vehicles (CAVs) have gathered considerable momentum and research attention. Generally, such problems present…
Velocity Obstacle Based Risk-Bounded Motion Planning for Stochastic Multi-Agent Systems
Xiaoxue Zhang, Jun Ma, Zilong Cheng +2
In this paper, we present an innovative risk-bounded motion planning methodology for stochastic multi-agent systems. For this methodology, the disturbance, noise, and model uncerta…
Towards Generalized and Incremental Few-Shot Object Detection
Yiting Li, Haiyue Zhu, Jun Ma +4
Real-world object detection is highly desired to be equipped with the learning expandability that can enlarge its detection classes incrementally. Moreover, such learning from only…
Receding Horizon Motion Planning for Multi-Agent Systems: A Velocity Obstacle Based Probabilistic Method
Xiaoxue Zhang, Jun Ma, Zilong Cheng +2
In this paper, a novel and innovative methodology for feasible motion planning in the multi-agent system is developed. On the basis of velocity obstacles characteristics, the chanc…