针对现有人机交互系统中的力觉交互沉浸感不足的问题,提出了一种基于分布式系统的动态碰撞检测与虚拟力觉交互的控制策略。力觉交互系统采用分布式设计,主要包括:人机交互接口管理、空间位形解算和运动控制与碰撞检测等单元设计。在交...针对现有人机交互系统中的力觉交互沉浸感不足的问题,提出了一种基于分布式系统的动态碰撞检测与虚拟力觉交互的控制策略。力觉交互系统采用分布式设计,主要包括:人机交互接口管理、空间位形解算和运动控制与碰撞检测等单元设计。在交互过程中,采用分层方式处理碰撞效果。根据模型所处虚拟空间的相对几何位置与碰撞后的运动状态构建虚拟力觉,并由交互管理单元映射至实体交互设备,实现操作者的力觉感知与交互。采用PHANTOM omni力反馈设备与Visual Studio 2010构建了动态碰撞检测的仿真实验系统,并进行了虚拟力觉交互实验。实验结果表明:操作者通过力反馈设备能够实现力觉感知与交互,有效解决了交互过程中的力觉效果不足的问题。展开更多
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
文摘针对现有人机交互系统中的力觉交互沉浸感不足的问题,提出了一种基于分布式系统的动态碰撞检测与虚拟力觉交互的控制策略。力觉交互系统采用分布式设计,主要包括:人机交互接口管理、空间位形解算和运动控制与碰撞检测等单元设计。在交互过程中,采用分层方式处理碰撞效果。根据模型所处虚拟空间的相对几何位置与碰撞后的运动状态构建虚拟力觉,并由交互管理单元映射至实体交互设备,实现操作者的力觉感知与交互。采用PHANTOM omni力反馈设备与Visual Studio 2010构建了动态碰撞检测的仿真实验系统,并进行了虚拟力觉交互实验。实验结果表明:操作者通过力反馈设备能够实现力觉感知与交互,有效解决了交互过程中的力觉效果不足的问题。
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.
