8 citations · 14 across the 3 of their papers we have counts for
7 papers
AES: Autonomous Excavator System for Real-World and Hazardous Environments
Jinxin Zhao, Pinxin Long, Liyang Wang +5
Excavators are widely used for material-handling applications in unstructured environments, including mining and construction. The size of the global market of excavators is 44.12…
Optimization-Based Framework for Excavation Trajectory Generation
Yajue Yang, Pinxin Long, Jia Pan +2
In this paper, we present a novel optimization-based framework for autonomous excavator trajectory generation under various objectives, including minimum joint displacement and min…
Time Variable Minimum Torque Trajectory Optimization for Autonomous Excavator
Yajue Yang, Jia Pan, Pinxin Long +2
In this paper, we present a minimal torque and time variable trajectory optimization method for autonomous excavator considering the soil-tool interaction. The method formulates th…
Learning Resilient Behaviors for Navigation Under Uncertainty
Tingxiang Fan, Pinxin Long, Wenxi Liu +3
Deep reinforcement learning has great potential to acquire complex, adaptive behaviors for autonomous agents automatically. However, the underlying neural network polices have not…
Getting Robots Unfrozen and Unlost in Dense Pedestrian Crowds
Tingxiang Fan, Xinjing Cheng, Jia Pan +4
We aim to enable a mobile robot to navigate through environments with dense crowds, e.g., shopping malls, canteens, train stations, or airport terminals. In these challenging envir…
Fully Distributed Multi-Robot Collision Avoidance via Deep Reinforcement Learning for Safe and Efficient Navigation in Complex Scenarios
Tingxiang Fan, Pinxin Long, Wenxi Liu +1
In this paper, we present a decentralized sensor-level collision avoidance policy for multi-robot systems, which shows promising results in practical applications. In particular, o…