基于面向对象 Petri 网的水下机器人体系结构建模与可达性问题研究

A rolling velocity control method for a spherical mobile robot is implemented.Nonlinear relationships between the control-input and state-output of the spherical mobile robot are hard to be described by exact mathematical model.With the radial basis function neural network,nonlinear mapping from the inputs to outputs of the robot are established by online training.Thereafter the velocity controller of the robot is designed by feedback linearization method,and it is composed of a feedback linearization controller and a compensation controller for reducing approximation errors of neural network.The implementation of the controller is given.Experiments show that the velocity control for the spherical mobile robot can be achieved stably by this method.

Based on the widely used probabilistic grid map, a localizability estimation method for mobile robots is pro- posed. Firstly, the Fisher information matrix (FIM) of robot localization is transformed into discrete form, and a static localizability matrix suitable for off-line estimation based on the known grid map is obtained. On this basis, the impact factor of locally sensed unkown obstacles is adopted to modify the static localizability matrix, and a dynamic localizability matrix is proposed for on-line estimation to deal with unexpected dynamic changes of environments. This matrix describes both the localizability index and localizability direction of mobile robots quantitatively. The results of real robot experiments under different typical environments demonstrate the validity of the proposed method.

An obstacle-avoidance navigation algorithm based on bug algorithm is proposed for the vehicle using non-360 range sensors and having minimum turning radius.Then the vehicle can bypass obstacle edge along a continuous and smooth path and complete the fixed-goal navigation task.This algorithm uses "virtual antenna" to intuitively represent passable state in the front.The "tentacle algorithm" is used to analyze turning state,and the minimum turning radius of the vehicle is changed according to the surrounding environment to correct the turning route in real time.The test result on a Pioneer 3-AT wheeled robot show that the robot using the proposed algorithm can reach the fixed goal in an unknown environment without collision,and the trajectory is continuous and smooth.The algorithm solve the problem that bug algorithm cannot be used in this kind of vehicles.

The hyperelastic stress-strain constitutive model of the gastrointestinal tissues is introduced.According to the special characteristics of the gastrointestinal biomechanism,a locomotion gait based on anchoring-extending is proposed for the gastrointestinal micro robot.The relationship between the speed of single cabin and the resistance force is established through studying the mechanical interaction between single cabin of the micro robot and the intestinal tissues,and the locomotion efficiency of the robot is established through studying the mechanical interaction between the entire robot and the intestine.A critical step model based on the hyperelastic constitutive model is deduced based on the above mechanical analyses.This model is a guide for robot design and parameter optimization.Finally,the relationship between the robot’s single cabin speed and the tension force is obtained through robot model experiments,and the critical step model is verified in an in-vitro experiment with a robot prototype.

Aiming at the precise positioning of autonomous underwater vehicle(AUV) during submerged operation for long periods of time,an underwater terrain matching positioning method based on maximal likelihood estimation(MLE) is proposed.In this method,multibeam echo sounder(MBES) is taken as the underwater terrain measuring means,and maximum likelihood algorithm is used for correlation analysis of terrain character.For the influence from false peaks of likelihood function at flat bottom area,the Fisher criterion is introduced to restrict it.The false peaks are eliminated effectively and the discrimination of flat bottom area is enhanced.The simulation results based on one electronic chart data and sea test data from a multibeam echo sounder show that the proposed method is effective and feasible.

面向显微操作的混合驱动式微小型机器人的开发与应用

The globally K-exponentially stable path following control of an underactuated autonomous surface vehicle (ASV) is proposed based on the cascaded approach.The dynamics model of the ASV path following errors is derived utilizing the Serret-Frenet coordinate originated at the free path reference point, which creates an added control input, i.e., the change rate of the path parameter, to avoid the singularity problem when adopting the coordinate originating at the orthogonal projection point.The path following reference yaw is designed, and the whole path following model is decomposed into two cascaded sub-models, named the position tracking sub-model and the yaw angle and surge velocity tracking sub-model.The global K-exponential stability of the path following errors is proved using the cascaded system theory with the globally exponentially stable yaw angle and surge velocity tracking controllers.The results of the mathematic simulations and the lake trials of a real ASV demonstrate the performance of the proposed path following control algorithm.