In this paper,we present a distributed framework for the lidar-based relative state estimator which achieves highly accurate,real-time trajectory estimation of multiple Unmanned Aerial Vehicles(UAVs)in GPS-denied envi...In this paper,we present a distributed framework for the lidar-based relative state estimator which achieves highly accurate,real-time trajectory estimation of multiple Unmanned Aerial Vehicles(UAVs)in GPS-denied environments.The system builds atop a factor graph,and only on-board sensors and computing power are utilized.Benefiting from the keyframe strategy,each UAV performs relative state estimation individually and broadcasts very partial information without exchanging raw data.The complete system runs in real-time and is evaluated with three experiments in different environments.Experimental results show that the proposed distributed approach offers comparable performance with a centralized method in terms of accuracy and real-time performance.The flight test demonstrates that the proposed relative state estimation framework is able to be used for aggressive flights over 5 m/s.展开更多
Autonomous fight is a fundamental problem for various saplications of miaro aerial vehicles(MAVs).Thanks to the dewvelopment of Gudance.Navigation and Control(GNC)techndogle,the rsearch on this problem i abo becoming ...Autonomous fight is a fundamental problem for various saplications of miaro aerial vehicles(MAVs).Thanks to the dewvelopment of Gudance.Navigation and Control(GNC)techndogle,the rsearch on this problem i abo becoming mature.However,safe fight in unknown,dut tered enviouments remains an open question,epeaially with real-time reguirement on onboard computer.This paper propoes a framnework including prlelly mapping and planning and implements it on Graphics Pmocessing Unit(GPU).First,a spherical coomlinate proijection is used in the ocupency grid map to avold menory cnflicts.After that,in the planning phase,a method baed on latice state space sampling is applied to obtain mutiple rajectorfe parlelly.Then,we design a series of aoft constraints to ensure that the MAV is in a safe known space with optimal dynamics.By solving the cost for each trajectory and comparison,the optimal trajectory can be generated.The efectivenes of the propeed strategy is demonstrated through simulation testa.展开更多
基金supported by the National Key Research and Development Program of China(No.2018AAA0102401)the National Natural Science Foundation of China(Nos.62022060,61773278,61873340).
文摘In this paper,we present a distributed framework for the lidar-based relative state estimator which achieves highly accurate,real-time trajectory estimation of multiple Unmanned Aerial Vehicles(UAVs)in GPS-denied environments.The system builds atop a factor graph,and only on-board sensors and computing power are utilized.Benefiting from the keyframe strategy,each UAV performs relative state estimation individually and broadcasts very partial information without exchanging raw data.The complete system runs in real-time and is evaluated with three experiments in different environments.Experimental results show that the proposed distributed approach offers comparable performance with a centralized method in terms of accuracy and real-time performance.The flight test demonstrates that the proposed relative state estimation framework is able to be used for aggressive flights over 5 m/s.
基金supported by the National Natural Science Foundation of China under Grant Nos.62022060,62073234 and 61873340.
文摘Autonomous fight is a fundamental problem for various saplications of miaro aerial vehicles(MAVs).Thanks to the dewvelopment of Gudance.Navigation and Control(GNC)techndogle,the rsearch on this problem i abo becoming mature.However,safe fight in unknown,dut tered enviouments remains an open question,epeaially with real-time reguirement on onboard computer.This paper propoes a framnework including prlelly mapping and planning and implements it on Graphics Pmocessing Unit(GPU).First,a spherical coomlinate proijection is used in the ocupency grid map to avold menory cnflicts.After that,in the planning phase,a method baed on latice state space sampling is applied to obtain mutiple rajectorfe parlelly.Then,we design a series of aoft constraints to ensure that the MAV is in a safe known space with optimal dynamics.By solving the cost for each trajectory and comparison,the optimal trajectory can be generated.The efectivenes of the propeed strategy is demonstrated through simulation testa.
