Studies On Mobile Robot Localization Under Communication Protocol And Different Characteristic Constraints Of Sensors

Mobile robot localization(MRL)problem has always been a challenging research direction in the fields of control and signal processing.In the MRL system,the emergence of some new phenomena caused by different characteristics of sensors(mainly measurement outliers and the missing measurement induced by insufficient sensor energy)and the use of various types of communication protocols result in the existing MRL algorithms no longer applicable,which brings new challenges to MRL problem.Therefore,in view of the different characteristic constraints of sensor and different types of communication protocols,it is necessary to devise new solutions for MRL problems,which can not only enrich and extend the filtering theory,but also have practical engineering significance.In this thesis,MRL problems based on communication protocols and different characteristic constraints of sensor are studied,mainly including MRL problem un-der the sensor with the ability of harvesting energy,MRL problems under different types of communication protocols,measurement outlier-resistant MRL problem and MRL problem with multi-objective constraints under the dynamic event triggering mechanism.For coping with these problems,in this thesis,by designing differen-t types of filters/estimators which can meet the given performance requirements,the corresponding filter/estimator design mechanisms can be obtained,and then the corresponding solutions to MRL problems are put forward in terms of the acquired filter/estimator design schemes.Specifically,the research contents of this paper are as follows:·The MRL problem is studied under single sensor with the ability of harvesting energy.Consider a specific case that the sensor which can absorb energy from the external environment is installed on the mobile robot plant.When the sensor energy is sufficient,the sensor can produce measurement and send it to the filter.Otherwise,the missing measurement induced by insufficient sensor energy will occur.For the sake of deriving the missing measurement rate,the probability distribution of sensor energy level is obtained recursively.An upper bound(UB)of the localization error covariance(LEC)is acquired by employing the recursive filtering approach,and then the derived UB is minimized by appropriately choosing the appropriate filter gain.According to the proposed filter design scheme,the MRL algorithm under single sensor with the ability of harvesting energy is developed.·The MRL problem is investigated under multiple sensors with the ability of harvesting energy.Multiple sensors with the ability of harvesting energy in-stalled on the mobile robot plant are used to produce measurements.When the sensor has sufficient energy,the sensor can output measurement and send it to the local filter.Otherwise,the missing measurement induced by insufficient sensor energy will occur.In order to obtain the missing measurement rate,the probability distribution of energy level of each sensor is acquired recursively.A UB of the local LEC is obtained by using the recursive filtering method,and then such a UB is minimized by adequately designing the filter gain.At the end,the covariance intersection fusion scheme is used to fuse the obtained local localization information to complete the MRL.·The measurement outlier-resistant MRL problem is discussed.For the sake of restricting the impact of measurement outliers on the localization performance of the mobile robot,a time-varying state estimator is constructed,where a saturation function with variable saturation levels is contained to restrain the innovation.By designing the time-varying state estimator,the localization er-ror dynamic system can be guaranteed to satisfy the given H_?performance constraints over a finite horizon,such that an effective method for solving the MRL problem can be obtained.Firstly,by constructing an appropriate Lya-punov function,a sufficient condition is obtained which can ensure the local-ization error dynamic system meeting the given H_?performance constraints.Then,the designed state estimator gain can be obtained by the solution to cer-tain recursive linear matrix inequalities(RLMIs).According to the proposed filter design scheme,the measurement outlier-resistant MRL algorithm is given.·The MRL problem against measurement outliers of Doppler azimuth radars is investigated under the Round-Robin protocol.In the considered MRL prob-lem,the Doppler azimuth radars installed on the mobile robot plant are used to produce the Doppler frequency shift and azimuth containing the state infor-mation of the mobile robot.For the sake of alleviating the communication link congestion,the Round-Robin protocol is employed to govern the transmission of measurement data.In order to restrain the impact of measurement outliers on the localization performance,a time-varying state estimator is construct-ed,where a saturation function with variable saturation levels is included to restrain the innovation.By constructing an appropriate Lyapunov function,a sufficient condition is obtained,which can guarantee the localization error dy-namic system meeting the pre-specified H_?performance requirement.Then,in the light of the solution to a set of RLMIs,the constructed state estimator is devised.According to the proposed estimator design scheme,the measurement outlier-resistant MRL algorithm under the Round-Robin protocol is presented.·The MRL problem under the stochastic communication protocol is studied.Multiple Lidar sensors installed on the mobile robot plant are employed to produce measurements including distance and azimuth.In order to reduce the burden of network,the stochastic communication protocol is introduced to schedule the transmission of measurement data.Under the stochastic com-munication protocol,a time-varying filter is designed,which can ensure the filtering error system meeting the given H_?performance requirement over a fi-nite horizon such that the solution to the MRL problem can be found.Firstly,a Markov chain is introduced to model the transmission of the measurement data under the stochastic communication protocol.Then,by the mean of the stochastic analysis technique and the completing square approach,the desired time-varying filter is designed by solving two coupled backward discrete recur-sive Riccati equations.According to the proposed filter design scheme,the MRL algorithm under the stochastic communication protocol is summarized.·The MRL problem is studied under the dynamic event triggering mechanism and the case of filter gain disturbance existence,where the localization perfor-mance can simultaneously meet multi-objective constraints.For saving energy and avoiding waste of network bandwidth,the dynamic event triggering mech-anism is introduced to manage the measurement data transmission between the sensor and the filter.In order to characterize the filter gain fluctuation,a re-silient mechanism is introduced when designing the filter.The MRL problem is solved by designing a nonlinear resilient filter which can ensure the localization error dynamics,over the finite horizon,meeting both H_?performance require-ment and error variance constraint simultaneously.By using Lyapunov theory and stochastic analysis technique,a sufficient condition is acquired which can guarantee the localization error dynamic system satisfying the given perfor-mance requirements simultaneously.Then,the filter is designed by using the LMI method.Based on the proposed filter design scheme,the corresponding MRL algorithm is summarized.