Research On Some Key Techniques Of Multi-Robot Formation Navigation

Multi-robot system is an exciting and challenging new field of the robotics;itinvolves biology,management,distributed artificial intelligence and cybernetics.The research of the multi-robot cooperation is an important component of themulti-robot system which studies the cooperative behavior,information interactionand evolutionary mechanism from the system aspect.This thesis focuses on theformation navigation which is a typical subject of the multi-robot cooperation and canbe widely applied to military,succor and soccer robot fields.Multi-robot formation navigation depends on some key technologies which therobot group apperceives through and navigates toward the destination.This researchstudies on these key technologies of cooperative localization,obstacle avoidance,information interaction and cooperative formation.Cooperative localization is an important and basic component of the formationnavigation,whose precision and real-time capability will impact the quality of theformation navigation directly.This thesis proposes a cooperative localization schemebased on multisensor fusion,and a joint filter model is constructed which is composedof three sub-filters and a main filter.First,the motion state function is deduced byfusing the odometer and gyroscope.Then,the target information is extracted from theimage by using the CMVision algorithm and the object detection algorithm which istrained by the Adaboost algorithm with Haar-like features.The localizationinformation of the target will be calculated by using the camera calibration algorithm.The laser scanner obtains the localization information by fusing the angle informationfrom the vision sensor.Lastly,the proposed joint filter model fuses the sensorsub-systems to obtain the precise localization of the target.Based on the cooperative localization,this thesis studies on the obstacleavoidance of the formation robots and proposes an obstacle avoidance scheme basedon the obstacle motion prediction.The motion state of the moving obstacle isdescribed using the Constant Velocity (CV) model,the Constant Accelerate (CA)model and the Current Statistical (CS) model.A Kalman-based Interacting MultipleModel (IMM) filter is adopted to estimate the obstacle motion trend.This avoidancefield is divided into three areas:Path Planning Area (PPA),Normal Avoidance Area(NAA) and Urgent Escape Step (UES).An improved Artificial Potential Field (APF), a normal avoidance strategy and an escaped algorithm are designed to avoid anyobstacles who invade into the relevant area.Information interaction is another key technology of the multi-robot system.Themulti-robot requests different throughput and real-time capability when implementingdifferent tasks.This thesis proposes a real-time data transmission model over Ad HocNetwork based on the bandwidth prediction.This transmission model is composed ofCross-Layer,Feedback and Bayesian network techniques.The sender extracts theimpact factors of the data transmission by using Cross-Layer method and Feedbackmethod.According to those relevant factors,this thesis constructs a Bayesian networkprediction model and predicts the bandwidth of the next period.The predictedbandwidth would be then used for the flow control of the sender.Based on the aforementioned key technologies,an optimal efficiency model isproposed for the multi-robot formation transform.The formation transform is dividedinto a static transform mode and a dynamic transform mode,and the formation energyconsumption (FEC) and the formation convergence time (FCT) are adopted toevaluate the efficiency of the formation transform.The optimal FEC model is aminimization model which minimizes the displaced distance sum of every robot.Theoptimal FCT model is a max-min model which minimizes the maximal displaceddistance of the robot.The efficiency model of the dynamic transform is subjected tothe constraint that the geometry center of the formation must move forward thepositive direction and a fixed range.The optimal space position and formationtransform efficiency are then obtained by solving the efficiency model.Lastly,we summarize the general work of this thesis and propose a short outlookon possible future research.