Research On Logistics Robot Cooperative Tracking System Based On Ultra-Wideband(UWB)Technology

With the explosive growth of the e-commerce industry,the logistics industry is undergoing a huge transformation.Robots,cloud warehouses and drones have all participated in the reform of the logistics industry and accelerated the intelligent process of the logistics industry.Tracking and positioning is a key technology in the field of robot navigation,and it is also a prerequisite for robots to make other behavioral decisions.In the intelligent logistics system,each logistics robot can effectively carry out tactical coordination and cooperation only by determining the location information of itself and its companions,and improve the efficiency and safety of executing tasks.Therefore,this paper uses multiple TurtleBot2 mobile robots as logistics robots,and deeply studies the cooperative tracking and positioning problem of multi-mobile robots based on ultra-wideband(UWB)technology.The main results of the research work are as follows:(1)A multi-mobile robot cooperative tracking system based on ultra-wideband(UWB)technology is constructed.Firstly,the master machine is used to remotely control the random motion of multiple mobile robots.The robot effectively avoids static and random dynamic obstacles in the environment during the motion.And Ultra-wideband(UWB)sensors are used to obtain distance information between the robot and the robot,the robot and the anchor point in real time.Then,the obtained distance information is substituted into the proposed ranging error weakening algorithm to effectively weaken the LOS and NLOS errors to obtain a distance estimation value.Finally,the sensor data fusion is carried out,that is,the distance estimation value is integrated into the cooperative tracking algorithm,and the position information of each robot at any time is estimated.Thereby achieving coordinated tracking of multiple mobile robots.(2)In order to reduce the influence of line of sight(LOS)and non-line of sight(NLOS)in the indoor environment on the ranging accuracy of ultra-wideband(UWB)sensors.A bayesian filtering approach for error Mitigation in Ultra-Wideband ranging is proposed.First,a large amount of data is collected under various propagation and obstacle material properties,and a probabilistic sensor model RSS and TOA are established.Then,under the Bayesian filter framework,the RSS sensor model is used to calculate the probability of the measured data under various propagation and obstacle material properties.On this basis,the distance probability density function is obtained by combining the TOA sensor model.Finally,by calculating the expectation of the distance probability density function,the ranging error can be weakened to obtain an accurate distance estimate.(3)A collaborative particle filter algorithm based on Gibbs sampling is designed.However,the multi-mobile robot system is a nonlinear,non-Gaussian system,so the state estimation based on the non-parametric particle filter algorithm is used.When the particle filter algorithm is applied in a multi-robot system,the state space dimension of the system increases exponentially with the increase of the number of robots,and the problem of "dimensionality disaster" will occur.So the joint posterior probability density function of the system is too complex to be directly sampled.The Gibbs sampling based on conditional distribution only considers the distribution of univariates,and the distribution of other variables is constant,which has the purpose of"dimension reduction".Therefore,the Gibbs sampling and particle filter algorithm are combined to design a collaborative particle filter algorithm based on Gibbs sampling,which greatly improves the practicability and accuracy of the system.The experimental results of cooperative tracking of multiple mobile robots based on UWB technology show that the range error mitigation algorithm based on Bayesian filtering and the cooperative particle filter algorithm based on Gibbs sampling are effective and accurate in real scene.