Name: the modular design and production of an intelligent robot based on a closed-loop control strategy
Uploaded: 2017-10-14T13:00:00
Description: Watch this Scientific Journal Video about The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy at JoVE.com

The authors would like to express their gratitude to Mr. Yaojie He for his assistance in performing the experiments reported in this paper. This work was supported in part by the National Natural Science Foundation of China (No. 61673117).

1. Construction of the Machine

<ol>
	<li>Assemble the chassis as illustrated, securing mechanical components using appropriate fasteners. (Figure 1) 
	NOTE: The chassis, which comprises the baseboard, motor, wheels, etc., is the primary component of the robot responsible for its motion. Thus, during assembly, keep the bracket straight.</li>
	<li>Tin the wire lead and both the positive and negative electrodes. Solder two wire leads onto the two ends of the motor, connecting the...

<ol>
	<li>Charalampous, K., Kostavelis, I., Gasteratos, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Robot+navigation+in+large-scale+social+maps:+An+action+recognition+approach.">Robot navigation in large-scale social maps: An action recognition approach.</a> Expert Syst Appl. 66 (1), 261-273 (2016).</li><li>Huang, Y., &amp;Wang, Q. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Disturbance+rejection+of+Central+Pattern+Generator+based+torque-stiffness-controlled+dynamic+walking.">Disturbance rejection of Central Pattern Generator based torque-stiffness-controlled dynamic walking.</a> Neurocomputing. 170 (1), 141-151 (2015).</li><li>Tepljakov, A., Petlenkov, E., Gonzalez, E., Belikov, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+Realization+of+Retuning+Fractional-Order+Controllers+for+an+Existing+Closed-Loop+Control+System.">Digital Realization of Retuning Fractional-Order Controllers for an Existing Closed-Loop Control System.</a> J Circuit Syst Comp. 26 (10), 32-38 (2017).</li><li>Siluvaimuthu, C., Chenniyappan, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Low-cost+Reconfigurable+Field-programmable+Gate+Array+Based+Three-phase+Shunt+Active+Power+Filter+for+Current+Harmonic+Elimination+and+Power+Factor+Constraints.">A Low-cost Reconfigurable Field-programmable Gate Array Based Three-phase Shunt Active Power Filter for Current Harmonic Elimination and Power Factor Constraints.</a> Electr Pow Compo Sys. 42 (16), 1811-1825 (2014).</li><li>Brogardh, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Present+and+future+robot+control+development+-+An+industrial+perspective.">Present and future robot control development - An industrial perspective.</a> Annu Rev Control. 31 (1), 69-79 (2007).</li><li>Wang, E., Huang, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Novel+DoubleClosed+Loops+Control+of+the+Three-phase+Voltage-sourced+PWM+Rectifier.">A Novel DoubleClosed Loops Control of the Three-phase Voltage-sourced PWM Rectifier.</a> Proceedings of the CSEE. 32 (15), 24-30 (2012).</li><li>Li, D. H., Chen, Z. X., Zhai, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Double+Closed-Loop+Controller+Design+of+Brushless+DC+Torque+Motor+Based+on+RBF+Neural+Network.">Double Closed-Loop Controller Design of Brushless DC Torque Motor Based on RBF Neural Network.</a> , 1351-1356 (2012).</li><li>Tian, H. X., Jiang, P. L., Sun, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Double-Loop+DCSpeed+Regulation+System+Design+Basd+On+OCC).">Double-Loop DCSpeed Regulation System Design Basd On OCC).</a> , 889-890 (2014).</li><li>Xu, G. Y., Zhang, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Double+Closed-Loop+Feedback+Controller+Design+for+Micro+Indoor+Smart+Autonomous+Robot).">Double Closed-Loop Feedback Controller Design for Micro Indoor Smart Autonomous Robot).</a> , 474-479 (2011).</li><li>Chen, Y. N., Xie, B., Mao, E. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electric+Tractor+Motor+Drive+Control+Based+on+FPGA.">Electric Tractor Motor Drive Control Based on FPGA.</a> , 271-276 (2016).</li><li>Zhang, J., Zhou, Y. J., Zhao, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Study+on+Four-quadrant+Operation+of+Brushless+DC+Motor+Control+Method.">Study on Four-quadrant Operation of Brushless DC Motor Control Method.</a> Proc. International Conference on Mechatronics, Robotics and Automation. (ICMRA 2013). , 1363-1368 (2013).</li><li>Joice, C. S., Paranjothi, S. R., Kumar, V. J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+Control+Strategy+for+Four+Quadrant+Operation+of+Three+Phase+BLDC+Motor+With+Load+Variations.">Digital Control Strategy for Four Quadrant Operation of Three Phase BLDC Motor With Load Variations.</a> Ieee T Ind Inform. 9 (2), 974-982 (2013).</li><li>Drumheller, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimal+Decision+Making+Algorithm+for+Managed+Aquifer+Recharge+and+Recovery+Operation+Using+Near+Real-Time+Data:+Benchtop+Scale+Laboratory+Demonstration.">Optimal Decision Making Algorithm for Managed Aquifer Recharge and Recovery Operation Using Near Real-Time Data: Benchtop Scale Laboratory Demonstration.</a> Ground Water Monit R. 37 (1), 27-41 (2017).</li><li>Wang, X. S., GAO, Y., Cheng, Y. H., Ma, X. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Knowledge-guided+genetic+algorithm+for+path+planning+of+robot.">Knowledge-guided genetic algorithm for path planning of robot.</a> Control Decis. 24 (7), 1043-1049 (2009).</li></ol>

In this paper, we designed a type of intelligent robot that can be built autonomously. We implemented the proposed intelligent search algorithm and autonomous recognition by integrating several software programs with hardware. In the protocol, we introduced 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 stability of the structure, its ope...

Robots are complex, intelligent machines that combine knowledge of several disciplines, including mechanics, electronics, control, computers, sensors and artificial intelligence 1,2. Increasingly, robots are assisting or even replacing humans in the workplace, especially in industrial production, due to the advantages robots possess in performing repetitive or dangerous tasks. The design of the intelligent robot protocol in the current study is based on a closed-loop control strategy, specifically path planning based on a genetic algorithm. Furthermore, the functional modules have been strictly divided3,4, which may provide a solid foundation for future optimization work, so that the robots have a strong capacity for upgrades.
The modular implementation of the robotic platform is based primarily on the following methods: multi-dimensional combination control strategy in motor control module5,6, and intelligent exploration based on a genetic algorithm in the optimization algorithm module.
We use double closed-loop control of the DC motor and four-quadrant motor operation in the motor control module. Double closed-loop speed control means that the output of the speed regulator serves as the input of the current regulator, allowing it to control the current and torque of the motor. The advantage of this system is that the torque of the motor can be controlled in real-time based on the difference between the given speed and the actual speed. When the difference between given and actual speeds is relatively large, the motor torque increases and the speed changes faster to drive the motor speed toward the given value as quickly as possible, which makes for rapid speed regulation7,8,9. Conversely, when the speed is relatively close to the given value, it can automatically reduce the torque of the motor to avoid excessive speed, allowing the speed to achieve the given value relatively quickly with no error6,10. Since the equivalent time constant of the electric current loop is relatively small, the four-quadrant motor11,12 can respond more quickly to suppress the impact of interference when the system is subject to external interference. This allows it to improve the stability and anti-jamming ability of the system.
We choose a genetic intelligent optimization algorithm with the highest efficiency based on the results of a simulation run in MATLAB. A genetic algorithm is a stochastic parallel search algorithm based on the theory of natural selection in genetics. It constitutes an efficient method for finding the global optimal solution in the absence of any initial information. It regards the solution set of the problem as a population, thereby increasing the quality of the solution via continuous selection, crossover, mutation and other genetic operations. With regard to path planning by intelligent robots, difficulty arises as a result of insufficient initial information, complicated environments and nonlinearity. Genetic algorithms are better able to solve the problem of path planning because they possess global optimization ability, strong adaptability and robustness in solving nonlinear problems; there are no specific restrictions on the problem; the calculation process is simple; and there are no special requirements for the search space 13,14.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>L1-1</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>L2-1</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>L3-1</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>L4-1</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>L5-1</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>L5-2</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>U3A</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>U3B</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>U3C</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>U3F</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>U3G</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>U3H</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>U3J</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>I3</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>I5</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>I7</td>
			<td></td>
		</tr>
		<tr>
			<td>structural parts</td>
			<td>UPTECMONYH HAR</td>
			<td>CGJ</td>
			<td></td>
		</tr>
		<tr>
			<td>link component</td>
			<td>UPTECMONYH HAR</td>
			<td>LM1</td>
			<td></td>
		</tr>
		<tr>
			<td>link component</td>
			<td>UPTECMONYH HAR</td>
			<td>LM2</td>
			<td></td>
		</tr>
		<tr>
			<td>link component</td>
			<td>UPTECMONYH HAR</td>
			<td>LM3</td>
			<td></td>
		</tr>
		<tr>
			<td>link component</td>
			<td>UPTECMONYH HAR</td>
			<td>LM4</td>
			<td></td>
		</tr>
		<tr>
			<td>link component</td>
			<td>UPTECMONYH HAR</td>
			<td>LX1</td>
			<td></td>
		</tr>
		<tr>
			<td>link component</td>
			<td>UPTECMONYH HAR</td>
			<td>LX2</td>
			<td></td>
		</tr>
		<tr>
			<td>link component</td>
			<td>UPTECMONYH HAR</td>
			<td>LX3</td>
			<td></td>
		</tr>
		<tr>
			<td>link component</td>
			<td>UPTECMONYH HAR</td>
			<td>LX4</td>
			<td></td>
		</tr>
		<tr>
			<td>Steering gear structure component</td>
			<td>UPTECMONYH HAR</td>
			<td>KD</td>
			<td></td>
		</tr>
		<tr>
			<td>Steering gear structure component</td>
			<td>UPTECMONYH HAR</td>
			<td>DP</td>
			<td></td>
		</tr>
		<tr>
			<td>Infrared sensor</td>
			<td>UPTECMONYH HAR</td>
			<td>E18-B0</td>
			<td>Digital sensor</td>
		</tr>
		<tr>
			<td>Infrared&#160;Range&#160;Finder</td>
			<td>SHARP</td>
			<td>GP2D12</td>
			<td></td>
		</tr>
		<tr>
			<td>Gray level sensor</td>
			<td>SHARP</td>
			<td>GP2Y0A02YK0F</td>
			<td></td>
		</tr>
		<tr>
			<td>proMOTION&#160;CDS</td>
			<td>SHARP</td>
			<td>CDS&#160;5516</td>
			<td>The robot steering gear</td>
		</tr>
		<tr>
			<td>motor drive module</td>
			<td>Risym</td>
			<td>HG7881</td>
			<td></td>
		</tr>
		<tr>
			<td>solder wire</td>
			<td>ELECALL</td>
			<td>63A</td>
			<td></td>
		</tr>
		<tr>
			<td>terminal</td>
			<td>Bright wire</td>
			<td>5264</td>
			<td></td>
		</tr>
		<tr>
			<td>motor</td>
			<td>BX motor</td>
			<td>60JX</td>
			<td></td>
		</tr>
		<tr>
			<td>camera</td>
			<td>Logitech</td>
			<td>C270</td>
			<td></td>
		</tr>
		<tr>
			<td>Drilling machine</td>
			<td>XIN XIANG</td>
			<td>16MM</td>
			<td>Please be careful</td>
		</tr>
		<tr>
			<td>Soldering station</td>
			<td>YIHUA</td>
			<td>8786D</td>
			<td>Be&#160;careful&#160;to&#160;be&#160;burn</td>
		</tr>
		<tr>
			<td>screwdriver</td>
			<td>EXPLOIT</td>
			<td>043003</td>
			<td></td>
		</tr>
		<tr>
			<td>Tweezers</td>
			<td>R`DEER</td>
			<td>RST-12</td>
			<td></td>
		</tr>
	</tbody>
</table>

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 targets. 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 handling robot with an intelligent search algorithm and an 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 and a four-quadrant motor control strategy, with the aid of debugging software, as well as set steering gear identity (ID), baud rate and other working parameters to ensure that the robot achieves the 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 relevant algorithm, which can recognize the success of the robot&#39;s function for a given application.
The advantage of this approach is its reliability and flexibility, as the users can develop a variety of hardware construction programs and utilize the comprehensive debugger to implement an intelligent control strategy. This allows users to set personalized requirements based on their needs with high efficiency and robustness.

In the diagram of the double closed-loop motion control program, purple represents a given speed signal and yellow represents the value of the control system output. Figure 17 clearly shows that the double closed-loop control system is significantly more effective than an 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. ( Figure 1...

Watch this Scientific Journal Video about The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy at JoVE.com

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

We present a protocol on modular design and production of intelligent robots to help scientific and technical workers design intelligent robots with special production tasks based on personal needs and individualized design.

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 ...

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