空地机器人网络的同时视觉目标定位与分布式运动规划

项目名称： 空地机器人网络的同时视觉目标定位与分布式运动规划

项目编号： No.61503118

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化学科

项目作者： 邢关生

作者单位： 青岛科技大学

项目金额： 22万元

中文摘要： 项目面向空地机器人网络的视觉目标定位问题，研究同时的协同估计和运动规划方法，应对机器人运动能力和非线性非高斯目标为分布式定位策略设计提出的巨大挑战。工作包括：1）研究图像平面内融合ORB特征匹配和Camshift的运动目标快速检测方法，提高机器人视觉测量可靠性；2）研究具有平均一致性融合机制的分布式非线性滤波方法，在仅可局部邻居间通信的情况下，解决针对非线性非高斯运动目标的协同估计问题；3）以降低未来目标估计值的不确定性为目标，建立基于互信息的分布式非线性模型预测运动规划方法框架。创新之处在于提出有限时间一致分布式无迹粒子滤波方法，并通过信息论工具与分布式模型预测控制集成用于主动目标定位，应对了地面机器人的非完整约束和飞行机器人的欠驱动特点。研究成果具有重要科学意义和广泛的应用前景，为机器人网络系统设计与分析提供理论依据，加速空地协同机器人网络在安防、环境监视和搜索救援中的实用化进程。

中文关键词： 多机器人系统；空地协调；目标定位；分布式估计；协调控制

英文摘要： This proposal is focused on the research of simultaneous cooperative estimation and motion planning methods for active target localization problem of air-ground robotic networks to deal with the great challenges brought by motion constraints of robots and the property of nonlinear and non-Gaussian target to the design of distributed target localization strategies. The research work includes three parts.1) The fast detection method of moving targets will be discussed based on Camshift algorithm with ORB feature matching integrated to improve the performance of robotic visual measurements. 2）A new distributed nonlinear filtering method with average consensus-based fusion mechanism will be investigated to deal with the cooperative state estimation for nonlinear and non-Gaussian target under the condition that communications in the network only occur among local neighbors. 3) To reduce the uncertainty in future target state estimation, a distributed nonlinear model predictive motion planning framework will be proposed on the basis of mutual information. The creative contribution is that a finite-time-consensus-based distributed unscented particle filtering method will be proposed and its combination with distributed model predictive control method by using tools in information theory provides a solution to active target localization problem while the nonholonomic constraints of ground robots and underactuation of flying robots are considered. This research work has significant scientific insight and engineering value. The results will provide theoretical supports to the control system design and analysis of robotic networks, speed up the application of air-ground cooperative robotic networks in the field of security, environment monitoring and search and rescue.

英文关键词： multi-robot system;air-ground coordination;target localization;distributed estimation;coordinated control