The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Intelligent robots are part of a new generation of robots that are able to sense the surrounding environment, plan their own actions, and eventually reach their target. In recent years, reliance upon robots in both daily life and industry has increased. The protocol proposed in this paper describes the design and production of a humanoid robot with an intelligence search algorithm and autonomous identification function.

First, the various working modules are mechanically assembled to complete the construction of the work platform and the installation of the robotic manipulator. Then, we design a closed loop control system in a four quadrant motor control strategy with the aid of a debugging software called Robo Servo Terminal 2010 as well as Sat Steering Gear ID, Baud Rate and other working parameters to ensure that the robot achieves a desired dynamic performance and low energy consumption. Next, we debug the sensor to achieve multi-sensor fusion to accurately acquire environmental information.

Finally, we implement the relevance algorithm which can recognize the success of the robot's function for given application. The advantage of this approach is it's reliability and flexibility as the users can develop a variety of hardware construction programs and utilize the comprehensive debugger to implement intelligent control strategy. This allows users to set personalized requirements based on their needs, with high efficiency and robustness.

The construction of the machine. One, the chassis which comprises the baseboard, motor, wheels et cetera, is a primary component of the robot responsible for its motion. Thus, during assembly the bracket shall be kept straight.

Assemble the chassis as illustrated, securing mechanical components using appropriate fasteners. Two, ting the wire lead and both the positive and negative electrodes. Solder two wire leads onto the two ends of the motor, connection the red lead to the positive electrode and the black lead to the negative electrode.

Three, drill two holes. Three millimeters in diameter in the center of chassis to allow for installation of the motor driving module. Connect the motor to the motor driving module.

Drill one hole one centimeter from both the right and the left edges of the chassis for installation of bracket of infrared sensors on the bottom. Drill a hole 18 millimeters in diameter through each of the two structural components for the installation of sensors. Four, install the steering gear in symmetry.

Because of the large shock generated by the operation of steering gear, the bolts should be installed in manner that ensures a firm and impervious joint. Five, install four infrared sensors on the center of the machine. Six, place a 14.8 volt power supply in the center of the machine, and affix the microcontroller unit to the battery pack.

Seven, affix four REN sensors to the upper part of machine, adjust the angle between each sensor and the ground to 60 degrees. To guarantee detection accuracy relative to the working table. Eight, install the dual-axis tilt sensor which is used to detect the cases when the machine fails to reach its target in the working area.

Nine, use a screwdriver to attach the robot arm to the front of the machine. One, double click to open the robot server terminal to seldom and 10 debugging software. Connect the PC to the debug board with a USB converting cable, set the steering engine's Baud rate to 9, 600 beats per second, the rate limitation to 521 rounds per minute, the angular limitation to 300 degrees, and voltage limitation to 9.6 volts in the working interface.

Two, set the ID number of the two driving modules and the four steering engines. ID three and ID 4 are left blank for future updating purposes. Note, ID one, leftward driving module, ID two, rightward driving module, ID five, left front steering engine, ID six, right front steering engine, ID seven, left rear steering engine, ID eight, right rear steering engine.

Three, connect the sensors to your respective control interfaces. It should be noted that the sensor whose connector bears a triangular mark is G and D.One, rotate the regulating knob on the tail of the infrared sensors to adjust the detection range of the sensors, so that the robot can determine its location in the working table by analyzing the logic level of the infrared sensors. Two, debug the tilt angle sensor.

Position the tilt angle sensor horizontally and record these measured values. Incline the sensor towards two different directions and record its numeric values. If the measured values are within the arrow range, the sensor can be regarded as being in regular operation.

One, construct the simulation model of the DC motor. Based on the DC motor voltage balance equation, flux linkage equation and torque balance equation. Two, apply double closed-loop control of the DC motor.

Utilize the output of the speed regulator as an input to the current regulator to regulate the motor's torque and current. Three, apply four quadrant motion control of the DC motor. Four, utilize an HBR driving surrogate to achieve four-quadrant motion of the DC motor by modulating the on/off of MOSFET.

Five, apply pulsewise modulation to regulate the speed of the DC motor. Modulate the DC voltage pulsewise, applied to the motor armature by controlling the on/off of the electric switch when the voltage of DC motor power supply remains essentially unchanged. Thus, modulating the average value and the rotation speed input to armature voltage of the motor.

One, using USB download line to input the BIN file generate by Cal-5 into the controller. Two, select the program to be executed. Apply color regulation to categorize cargo in the factory.

One, use a large tag optical camera to collect images and verify the scan color using the number of the bonds to the dimensional area. Two, lift the object with the mechanical arms. Three, issue a command to transfer the object to the designated location using the camera and the driving motor of the robot.

Representative results in a diagram of the MATLAB simulating two, seven, and 14A, double closed-loop motion control program:It clearly shows that the double closed-loop control system is significantly more effective than open-loop system. The actual overshoot of the output of the double closed-loop system is relatively small and the dynamic performance of the system is better. In this paper we designed a type of intelligent robot that can be viewed autonomously.

We implemented the proposed intelligent search algorithm and autonomous recognition by integrating several software programs with hardware. In the product we introduced the basic approaches for configuring the hardware and debugging the intelligent robot which may help users design a suitable mechanical structure of their own robot. However, during actual operation, it is necessary to pay attention to the stability of the structure, its operating range, the degree of freedom and space utilization to ensure that these parameters meet the requirements.

One potential issue is the inability of the robot to actually achieve its desired functions. This may stem primarily from two causes:the first is the inability of the sensors to meet the requirements, to address the issues an additional level of debugging of the sensors may be necessary. Based on this situation or application, the second is the inability of the selected motor to meet the performance requirements.

When choosing a motor, priority must be given to a motor with suitable starting performance, operational stability and low noise within the budget. To begin design and production of a new robot, the parameters for manual configuration scheme must be defined to control the behavior of the new robot, so that it may adapt to the demands of the new task. Simultaneously, all processes must follow the steps presented in the protocol.

An advantage of the modular design of the robot lies in its clear division of work which allows it to be developed by the collaboration of various engineers. The work of each module can be developed independently to accomplish a specific task. We provide a basic design scheme for each module to help users search for the optimal scheme for a particular application.

The range of potential applications will expand considerably as intelligent robot technology matures. It will prove to be an invaluable resource to individuals in the field of ocean development, space exploration, industry, and agricultural production, social service and entertainment, to name a few. This technology will gradually replace human beings in dangerous and unsanitary work environments.

Intelligent robot will continue to develop toward multi-robot cooperation in intelligent and networked direction.