69 citations · 137 across the 9 of their papers we have counts for
9 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…
Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning
Pinxin Long, Tingxiang Fan, Xinyi Liao +3
Developing a safe and efficient collision avoidance policy for multiple robots is challenging in the decentralized scenarios where each robot generate its paths without observing o…
Deep-Learned Collision Avoidance Policy for Distributed Multi-Agent Navigation
Pinxin Long, Wenxi Liu, Jia Pan
High-speed, low-latency obstacle avoidance that is insensitive to sensor noise is essential for enabling multiple decentralized robots to function reliably in cluttered and dynamic…
DoraPicker: An Autonomous Picking System for General Objects
Hao Zhang, Pinxin Long, Dandan Zhou +10
Robots that autonomously manipulate objects within warehouses have the potential to shorten the package delivery time and improve the efficiency of the e-commerce industry. In this…