Research On Mobile Robot Navigation, Control Based On Multi-Sensor

As the robot application range extends constantly, its working condition is getting more and more complex, which is always unknown, dynamic and unstructured. So, it is a new challenge for robot to fulfill a mission in real time under these environments. The idea of mobile robot behavior control based on multi-sensor is put forward.according to a survey of the research on mobile robot control architectures and navigation technology, A mobile robot navigation control experiment system is built to study on environment perception, behavior decision, motion control and so on, in the objective-oriented mission mobile robot behavior control. The system consists of a mobile robot and a set of communication system. The main contents are as follows:A modularized distributed control system architecture based on multi-processor with parallel communication is put forward and employed in the hardware system design. Each module is controlled by an individual processor and the data processing is tackled by the same one processor.All modules run and communicate with each other in a parallel method, which improves the speed of data transmission.Deliberated/reactive hierarchical hybrid architecture is used in the software design, which consists of a human-machine interface layer,a mission planning layer and a behavior control layer.A distributed ultrasonic detecting system based on multi-processor is developed.It is composed of an upper working method control module and a lower intelligent ultrasonic ranging module array.Each intelligent ultrasonic ranging sensor is controlled by an individual micro-processor which achieves ranging data processing, and the intelligent ultrasonic ranging modules can be grouped to work in parallel mode, which enhances the real-time performance, which can restrain the ultrasonic crosstalk and random interference and improve the accuracy of the detecting system.The objective-oriented mission can also be accomplished utilizing visual perception. has two behavior modules:goal approaching behavior, control behavior and escape behavior,each module has a given priority.The behavior arbiter decides which behavior module can control the robot by their given priority when the behaviors are valid.Employing the above segmentation technique of visual localization in indoor environment based visual landmarks is conducted on image, Here visual landmarks are those doors of corridor is characterized by topological graph.and doorpalates in corridor.Since lifting wavelet transform is suited for image decomposition and Radon transform is fit for line detection, their excellent performances are put together to figure out line detection pattern. This method decrease complexity of count greatly, and reduce run time effectively.The correlative experimental results show that the method can obtain the accurate measurement.We proposed a path planning algorithm based on neural network for cleaning robots.In this algorithm, a discrete method is used to approximate the minus gradient direction of the energy. We combined the penalty function with the distance energy function to construct the cost function.The path planning is implemented by determinating the motion tendency of the points set. The parameter optimization of the algorithm is investigated through computersimulation.These provide valuable guidance for the application of the algorithm in practice.The study on mobile robot dynamic obstacles avoiding strategy in global navigation is carried out.Something that appeared on the path planned by is regarded as dynamic obstacles which are classified into motorial obstacles and static obstacles. The robot can distinguish the above dynamic obstacles by using the information of ultrasonic detecting system and active vision system.The robot can avoid the dynamic obstacles appeared in global navigation using different obstacle avoiding strategy. The motion trajectories of moving obstacles are predicted by using an auto regressive (AR) model, thus, dynamic path planning is translated into instantaneously static one. This method enables the robot give a quick response when encountering obstacles.A novel fuzzy controller with fuzzy non-linear Parameter is proposed. In order to solve the problems of time consuming and hard to satisfy the control demands when seeking the parameters.A non-liner fuzzy method is proposed to generate the parameters. Partiele swarm optimization (PSO) algorithm is used to generate the non-linear fuzzy rule base automatically without prior knowledge. The modularized distributed control system architecture based on multi-processor with parallel communication and manufacture methods show the characteristics of practicability and expansibility in intelligent robot research.