Motion control system and method of mobile robot in intelligent space

Abstract

The invention discloses a motion control system and method of a mobile robot in an intelligent space. The motion control system is composed of the intelligent space and the mobile robot. The intelligent space comprises a monitoring host, a distributed visual system and a wireless sensor network system based on Zigbee. The motion control method of the mobile robot in the intelligent space comprises the steps that pose information of the mobile robot is obtained at first; then control deviation e of the mobile robot is obtained; mobile robot multi-objective self-regulation PID motion control based on an RBF identification network is conducted at last. Compared with an existing mobile robot control system based on a vehicle-mounted video, the motion control system and method of the mobile robot in the intelligent space have the advantages of being small in calculated amount, good in instantaneity, and more accurate in motion control.

Description

Technical field [0001] The invention relates to the construction of a motion control system of a mobile robot in an intelligent space, in particular to a motion control method of a mobile robot. Background technique [0002] The intelligent space technology of the mobile robot is to distribute and install the sensing devices and actuators in the corresponding positions of the robot space, so as to realize the robot's comprehensive perception of people and objects in the space, thereby helping it to be faster, more accurate and more stable in an uncertain environment. navigation. The motion control of the mobile robot refers to the ability to quickly and accurately move to the predetermined target point along the path to be tracked by controlling its own driving mechanism according to the detected environmental information and its own motion state. Therefore, the motion control of the mobile robot in the intelligent space is to first use the global vision system in the intel...

AI Technical Summary

Problems solved by technology

[0004] (1) Although the movement of the robot includes position and direction, the two are carried out at the same time, and this patent is completed through the control of corner and movement respectively, which is not conducive to the continuity of the movement process of the robot;

[0005] (2) Corner and position control is realized based on polynomials, while the motion of a mobile robot is an incomplete constraint system, and it is difficult to accurately construct a motion control model for robot corners and positions with limited polynomials;

[0006] (3) Even if the polynomial is used to realize the motion control of the robot, how to select the degree and coefficient of the polynomial is very important, but this patent does not mention it;

[0007] (4) How to obtain the position of the robot and track the target position is the key to realizing the control strategy, which is not mentioned in this patent

[0009] (1) If the entire control of the robot is treated as a black box problem, and the nonlinear modeling is realized through the neural network, the requirements for the number of layers of the neural network model and the number of nodes of each layer are relatively high, and the patent does not mention how to select ;

[0010] (2) The use of neural networks for nonlinear modeling of robot motion control requires more accurate network weights and thresholds, which in turn requires a large number of learning samples, but it is difficult to obtain complete learning samples for motion systems. The patent also does not mention how to obtain sample data;

[0011] (3) Although the control strategy uses visual sensors to obtain environmental information, it uses a vehicle-mounted camera, which is not aimed at the research of robot motion control under the global vision system.

Compared with the global vision system, the processing data of the vehicle-mounted camera is larger, and it is difficult to meet the real-time requirements of the robot; in addition, the vehicle-mounted camera obtains local environmental information, the robot cannot achieve global path tracking, and the motion control accuracy is not high

[0012] In short, the motion control of mobile robots is a technical difficulty in the field of robotics. At present, the design of motion control systems and methods for mobile robots based on sensor devices in smart spaces is still very small.

In addition, the motion control of a mobile robot is still a multi-objective control problem, and it often adjusts its own posture continuously due to the need for obstacle avoidance during the movement process. The control method of self-adjustment is particularly important

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