1 citations · 1 across the 6 of their papers we have counts for
6 papers
Neural-Primitive: An Efficient End-to-end Local Planner with Primitive-based Imitation Learning for Autonomous Flight
Zhitao Liu, Guangtong Xu, Zihan Wang +3
Autonomous flight in unknown cluttered environments is hindered by the computation-quality-memory trilemma of onboard trajectory generation. In this paper, we propose an efficient…
FLIP: Real-Time and Resilient Formation Planning for Large-Scale DIstributed Swarms via Point Cloud Registration
Yuan Zhou, Guangtong Xu, Zhenyu Hou +2
Traditional large-scale formation planning either oversimplify the formation representation which leads to poor performance, or they employ complete collaborative relationships, wh…
Primitive-Swarm: An Ultra-lightweight and Scalable Planner for Large-scale Aerial Swarms
Jialiang Hou, Xin Zhou, Neng Pan +5
Achieving large-scale aerial swarms is challenging due to the inherent contradictions in balancing computational efficiency and scalability. This paper introduces Primitive-Swarm,…
Primitive-Planner: An Ultra Lightweight Quadrotor Planner with Time-optimal Primitives
Jialiang Hou, Neng Pan, Zhepei Wang +4
It is a significant requirement for a quadrotor trajectory planner to simultaneously guarantee trajectory quality and system lightweight. Many researchers focus on this problem, bu…
HGS-Planner: Hierarchical Planning Framework for Active Scene Reconstruction Using 3D Gaussian Splatting
Zijun Xu, Rui Jin, Ke Wu +6
In complex missions such as search and rescue,robots must make intelligent decisions in unknown environments, relying on their ability to perceive and understand their surroundings…
UniQuad: A Unified and Versatile Quadrotor Platform Series for UAV Research and Application
Yichen Zhang, Xinyi Chen, Peize Liu +5
As quadrotors take on an increasingly diverse range of roles, researchers often need to develop new hardware platforms tailored for specific tasks, introducing significant engineer…