CN117666454A - Juvenile programming robot based on artificial intelligence and control system thereof - Google Patents
Juvenile programming robot based on artificial intelligence and control system thereof Download PDFInfo
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Abstract
The invention relates to the technical field of programming robots, in particular to an artificial intelligence-based juvenile programming robot and a control system thereof, wherein the juvenile programming robot comprises a supporting bottom plate, a protective box is fixedly connected to the upper surface of the supporting bottom plate, a main board mask is fixedly connected to one side of the protective box, and a display panel is fixedly connected to the inside of one side of the main board mask, which is far away from the main board mask of the protective box; the invention performs combined evaluation analysis from three angles of the power supply end, the driving end and the executing end, and performs analysis by combining the interference evaluation coefficient R, so as to ensure the control effect and the operation safety of the robot, and simultaneously is beneficial to improving the accuracy of the analysis result, namely performing operation risk supervision analysis on the power supply data of the power supply end, the control method comprises the steps of carrying out feedback analysis on state data of a driving end to ensure normal operation and control of the robot, carrying out runaway risk assessment analysis on the state data of the driving end to ensure execution performance of the robot, and carrying out runaway risk assessment analysis on the state data of the driving end by combining the execution data of the driving end to ensure control effect of the robot.
Description
Technical Field
The invention relates to the technical field of programming robots, in particular to an artificial intelligence-based juvenile programming robot and a control system thereof.
Background
With the development of artificial intelligence interaction technology, more and more robots enter the field of vision of people, basic robot programming education helps the development of the manual capacity and logic thinking capacity of children greatly, simple robot programming is realized, and control of the children is not available, but the development of technology makes the robots become more and more intelligent, and the intelligent of the robots means that the robots have certain perception capacity, planning capacity, action capacity and coordination capacity, so that the robots are automatic machines with high flexibility, and therefore, the children can control the robots to execute corresponding programming content through simple programming operation, so that the manual capacity and logic capacity of the children are cultivated;
however, when the control effect of the robot is analyzed, the existing robot control system has the defects that the analysis data is too single, so that the error of the control analysis result is large, the control optimization management of the robot is not facilitated, the power supply condition of a battery in the robot cannot be monitored, the execution condition of a driving motor and an execution end of a driving end cannot be analyzed, the control stability and the safety of the robot cannot be analyzed by combining the power supply end, the driving end and the execution end, and the operation safety and the control effect of the robot are reduced;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide an artificial intelligence-based juvenile programming robot and a control system thereof, which solve the technical defects, and the invention performs combined evaluation analysis from three angles of a power supply end, a driving end and an execution end, performs analysis by combining an interference evaluation coefficient R so as to ensure the control effect and operation safety of the robot, is beneficial to improving the accuracy of an analysis result, namely, performs operation risk supervision analysis on power supply data of the power supply end so as to judge whether an internal battery of the robot is normal or not so as to ensure the normal operation and control of the robot, and performs feedback analysis on state data of the driving end so as to judge whether a driving motor is normal or not so as to ensure the execution performance of the robot, and performs out-of-control risk evaluation analysis by combining execution data of the execution end so as to judge whether the control effect of the robot reaches the standard or not so as to perform control optimization processing in time, and performs early warning in an information feedback manner so as to remind an operator to perform control optimization on the robot so as to ensure the control effect and operation safety of the robot.
The aim of the invention can be achieved by the following technical scheme: the utility model provides a juvenile programming robot based on artificial intelligence, includes supporting baseplate, supporting baseplate's last fixed surface is connected with the protection box, one side fixedly connected with mainboard face guard of protection box, one side inside fixedly connected with display panel that the protection box was kept away from to the mainboard face guard, one side top fixedly connected with early warning lamp that the mainboard face guard is close to display panel, both surfaces all rotate around supporting baseplate are connected with driving roller, driving roller's outside has cup jointed the chain strip, supporting baseplate's inside is provided with driving motor, and driving motor is connected with driving roller.
The system comprises a control panel, a data acquisition unit, a power supply risk unit, a disturbance control analysis unit, an execution performance unit, an integration feedback unit and an early warning display unit, wherein the control platform, the data acquisition unit, the power supply risk unit, the disturbance control analysis unit, the execution performance unit, the integration feedback unit and the early warning display unit are arranged in the display panel;
when the control platform receives an execution program and an execution instruction, a management instruction is generated and sent to the data acquisition unit, the data acquisition unit immediately acquires power supply data and influence data of the robot after receiving the management instruction, the power supply data comprise discharge current and discharge rate of an internal battery, the influence data comprise a line risk value and a delay risk value of an electric element, the power supply data and the influence data are respectively sent to the power supply risk unit and the disturbance control analysis unit, the power supply risk unit immediately carries out operation risk supervision analysis on the power supply data after receiving the power supply data, the obtained risk signal is sent to the early warning display unit, and the early warning display unit immediately displays preset early warning characters corresponding to the risk signal on the display panel after receiving the risk signal;
the disturbance control analysis unit immediately carries out disturbance supervision analysis on the influence data after receiving the influence data, sends the obtained disturbance evaluation coefficient R to the execution performance unit, sends the obtained disturbance signal to the early warning display unit, and immediately displays preset early warning characters corresponding to the disturbance signal on the display panel after receiving the disturbance signal;
the execution performance unit immediately acquires state data of the driving motor after receiving the interference evaluation coefficient R, wherein the state data comprises a rotating shaft friction value and a motor controller temperature value inside the driving motor, performs feedback analysis on the state data, sends an obtained execution performance evaluation coefficient Z to the integrated feedback unit, and sends an obtained abnormal signal to the early warning display unit;
and the integrated feedback unit immediately acquires the execution data of the robot after receiving the execution performance evaluation coefficient Z, wherein the execution data represents the execution duration of each execution action, carries out runaway risk evaluation analysis on the execution data, and sends the obtained normal signal and the obtained runaway signal to the early warning display unit.
Preferably, the operation risk supervision and analysis process of the power supply risk unit is as follows:
s1: collecting the duration of robot operation for a period of time, marking the duration as a time threshold, dividing the time threshold into i sub-time nodes, wherein i is a natural number larger than zero, acquiring the discharge rate of batteries in each sub-time node, constructing a set A of the discharge rate, acquiring a maximum subset and a minimum subset in the set A, and marking the difference value between the maximum subset and the minimum subset in the set A as a discharge span value;
s12: acquiring the discharge current of the battery in each sub-time node, acquiring the difference value between the discharge currents in the two connected sub-time nodes, marking the average value of the difference values between the discharge currents in the two connected sub-time nodes as a floating average value, comparing and analyzing the floating average value with a stored preset floating average value threshold value, and marking the ratio between the part of the floating average value larger than the preset floating average value threshold value and the preset floating average value threshold value as a floating risk value if the floating average value is larger than the preset floating average value threshold value;
s13: comparing the discharge span value and the floating risk value with a preset discharge span value threshold value and a preset floating risk value threshold value which are recorded and stored in the discharge span value and the floating risk value respectively, and analyzing the discharge span value and the floating risk value:
if the discharge span value is smaller than or equal to a preset discharge span value threshold value and the floating risk value is smaller than or equal to a preset floating risk value threshold value, no signal is generated;
and if the discharge span value is greater than a preset discharge span value threshold value or the floating risk value is greater than a preset floating risk value threshold value, generating a risk signal.
Preferably, the interference supervision and analysis process of the interference control analysis unit is as follows:
SS1: acquiring a line risk value of an internal line of the robot within a time threshold, wherein the line risk value represents a product value obtained by carrying out data normalization processing on a part of the running temperature of the line exceeding a stored preset running temperature and an average resistance value of a line port, comparing the line risk value with the stored preset line risk value, and if the line risk value is larger than the preset line risk value, marking a part of the line risk value larger than the preset line risk value as a line abnormal value XY;
SS2: acquiring a delay risk value YF of an internal electrical element of the robot within a time threshold, wherein the delay risk value represents a product value obtained by carrying out data normalization processing on a part of the internal electrical element of the robot, the operation resistance of which is larger than a stored preset operation resistance threshold, and an internal environment temperature value of the robot;
SS3: according to the formulaObtaining an interference evaluation coefficient, wherein a1 and a2 are preset scale factor coefficients of a line abnormal value and a delay risk value respectively, a1 and a2 are positive numbers larger than zero, a3 is a preset fault tolerance factor coefficient, the value is 1.449, and R is interferenceThe evaluation coefficient is compared with a preset interference evaluation coefficient threshold value which is recorded and stored in the interference evaluation coefficient R and the interference evaluation coefficient R, and analysis is carried out:
if the interference evaluation coefficient R is smaller than a preset interference evaluation coefficient threshold value, no signal is generated;
and generating interference signals when the interference evaluation coefficients R are larger than or equal to a preset interference evaluation coefficient threshold value.
Preferably, the feedback analysis process of the execution performance unit is as follows:
acquiring a rotating shaft friction value in a battery in each sub-time node, establishing a rectangular coordinate system by taking time as an X axis and taking the rotating shaft friction value as a Y axis, drawing a rotating shaft friction value curve in a dot drawing mode, drawing a preset rotating shaft friction value range value curve in the coordinate system, acquiring a ratio between the length value of a line segment of the rotating shaft friction value curve in the preset rotating shaft friction value range value curve and the total length of the line segment of the rotating shaft friction value curve from the coordinate system, and marking the ratio as a safety circumference value AY;
acquiring a temperature value of a motor controller in a battery in each sub-time node, constructing a set B of the temperature value of the motor controller, acquiring a mean value and a discrete coefficient of the set B, and marking a product value obtained by carrying out data normalization processing on the mean value and the discrete coefficient of the set B as a risk multiplier value FB;
obtaining an execution performance evaluation coefficient Z according to a formula, and comparing the execution performance evaluation coefficient Z with a preset execution performance evaluation coefficient threshold value recorded and stored in the execution performance evaluation coefficient Z:
if the ratio between the execution performance evaluation coefficient Z and the preset execution performance evaluation coefficient threshold is smaller than one, no signal is generated;
if the ratio between the execution performance evaluation coefficient Z and the preset execution performance evaluation coefficient threshold is greater than or equal to one, generating an abnormal signal.
Preferably, the process of the risk assessment analysis of the runaway of the integrated feedback unit is as follows:
acquiring the execution time length of each execution action of the robot in the time threshold, comparing the execution time length of each execution action with a stored preset execution time length threshold corresponding to the execution time length, and if the execution time length is longer than the preset execution time length threshold, acquiring the total number of the execution actions corresponding to the execution time length longer than the preset execution time length threshold, and marking the total number as an abnormal constant YC;
simultaneously, a discharge span value and a floating risk value are called from the power supply risk unit, and the discharge span value and the floating risk value are respectively marked as FD and FF;
according to the formulaObtaining a runaway risk assessment coefficient, wherein alpha, beta, epsilon and eta are respectively abnormal constants, execution performance assessment coefficients, discharge span values and preset influence factor coefficients of a floating risk value, alpha, beta, epsilon and eta are positive numbers larger than zero, S is the runaway risk assessment coefficient, and the runaway risk assessment coefficient S is compared with a preset runaway risk assessment coefficient threshold value recorded and stored in the runaway risk assessment coefficient S:
if the runaway risk assessment coefficient S is smaller than a preset runaway risk assessment coefficient threshold value, generating a normal signal;
and if the runaway risk assessment coefficient S is greater than or equal to a preset runaway risk assessment coefficient threshold value, generating a runaway signal.
The beneficial effects of the invention are as follows:
(1) The invention performs combined evaluation analysis from three angles of the power supply end, the driving end and the executing end, and performs analysis by combining the interference evaluation coefficient R to ensure the control effect and the operation safety of the robot, and is beneficial to improving the accuracy of the analysis result, namely performing operation risk supervision analysis on the power supply data of the power supply end to judge whether the internal battery of the robot is normal or not so as to ensure the normal operation and control of the robot, the control effect of the robot is judged to be up to standard by executing feedback analysis on the state data of the driving end, judging whether the driving motor runs normally so as to ensure the execution performance of the robot, and by executing out-of-control risk assessment analysis on the execution data of the execution end, so that the control optimization processing is timely carried out, and early warning is carried out in an information feedback mode so as to remind an operator to carry out control optimization on the robot, so that the control effect and the running safety of the robot are ensured;
(2) According to the invention, through performing interference supervision analysis on the influence data, whether the influence data influence the operation, the power supply stability and the control efficiency of the robot is judged, and further, when performing out-of-control risk assessment analysis, the influence data is combined for analysis, so that the accuracy of an analysis result is improved, and the operation safety and the control effect of the robot are guaranteed.
Drawings
The invention is further described below with reference to the accompanying drawings;
FIG. 1 is a perspective view of the structure of the present invention;
FIG. 2 is a top plan view of the structure of the present invention;
fig. 3 is a flow chart of the system of the present invention.
Legend description: 1. a support base plate; 2. a protective case; 3. a main board mask; 4. a display panel; 5. an early warning lamp; 6. driving the roller; 7. a chain strap.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1:
referring to fig. 1 to 3, the invention discloses an artificial intelligence-based juvenile programming robot, which comprises a supporting base plate 1, wherein a protection box 2 is fixedly connected to the upper surface of the supporting base plate 1, one side of the protection box 2 is fixedly connected with a main board mask 3, one side of the main board mask 3, which is far away from the protection box 2, is fixedly connected with a display panel 4, an alarm lamp 5 is fixedly connected to the upper side of one side of the main board mask 3, which is close to the display panel 4, the front surface and the rear surface of the supporting base plate 1 are both rotatably connected with a driving roller 6, a chain strip 7 is sleeved on the outer side of the driving roller 6, a driving motor is arranged in the supporting base plate 1 and is connected with the driving roller 6, namely, a programmed program is led into the robot to move according to the program, and the driving motor drives the driving roller 6 to rotate through an output end, so that the driving roller 6 drives the chain strip 7 to move, and the robot moves.
Example 2:
the control system of the juvenile programming robot based on artificial intelligence, the display panel is internally provided with a control platform, a data acquisition unit, a power supply risk unit, a disturbance control analysis unit, an execution performance unit, an integrated feedback unit and an early warning display unit, wherein the control platform is in one-way communication connection with the data acquisition unit, the data acquisition unit is in one-way communication connection with the power supply risk unit and the disturbance control analysis unit, the power supply risk unit and the disturbance control analysis unit are in one-way communication connection with the early warning display unit, the disturbance control analysis unit is in one-way communication connection with the execution performance unit, the power supply risk unit and the execution performance unit are in one-way communication connection with the integrated feedback unit, the execution performance unit is in one-way communication connection with the early warning display unit, and the integrated feedback unit is in one-way communication connection with the early warning display unit;
when the control platform receives an execution program and an execution instruction, a management instruction is generated and sent to the data acquisition unit, the data acquisition unit immediately acquires power supply data and influence data of the robot after receiving the management instruction, the power supply data comprise discharge current and discharge rate of an internal battery, the influence data comprise a line risk value and a delay risk value of an electric element, the power supply data and the influence data are respectively sent to the power supply risk unit and the disturbance control analysis unit, the power supply risk unit immediately carries out operation risk supervision analysis on the power supply data after receiving the power supply data so as to judge whether the internal battery of the robot is normal or not, so that the normal operation of the robot is ensured, the control effect on the robot is improved, and the specific operation risk supervision analysis process is as follows:
collecting the duration of robot operation for a period of time, marking the duration as a time threshold, dividing the time threshold into i sub-time nodes, wherein i is a natural number larger than zero, obtaining the discharge rate of batteries in each sub-time node, constructing a set A of the discharge rate, obtaining a maximum subset and a minimum subset in the set A, and marking the difference value between the maximum subset and the minimum subset in the set A as a discharge span value, wherein the discharge span value is an influence parameter reflecting the battery operation risk;
acquiring the discharge current of the battery in each sub-time node, acquiring the difference value between the discharge currents in the two connected sub-time nodes, marking the average value of the difference values between the discharge currents in the two connected sub-time nodes as a floating average value, comparing the floating average value with a stored preset floating average value threshold value, and analyzing the comparison result, if the floating average value is larger than the preset floating average value threshold value, marking the ratio between the part of the floating average value larger than the preset floating average value threshold value and the preset floating average value threshold value as a floating risk value, wherein the larger the value of the floating risk value is, the larger the abnormal risk of the power supply of the battery in the robot is;
comparing the discharge span value and the floating risk value with a preset discharge span value threshold value and a preset floating risk value threshold value which are recorded and stored in the discharge span value and the floating risk value respectively, and analyzing the discharge span value and the floating risk value:
if the discharge span value is smaller than or equal to a preset discharge span value threshold value and the floating risk value is smaller than or equal to a preset floating risk value threshold value, no signal is generated;
if the discharge span value is greater than a preset discharge span value threshold value or the floating risk value is greater than a preset floating risk value threshold value, generating a risk signal and sending the risk signal to an early warning display unit, wherein the early warning display unit immediately displays preset early warning characters corresponding to the risk signal on a display panel 4 after receiving the risk signal so as to remind an operator to reasonably control a battery in the robot, thereby ensuring the operation capacity and the operation control effect of the robot and reducing the risk of out of control of the robot;
the disturbance control analysis unit immediately carries out disturbance supervision analysis on the influence data after receiving the influence data, judges whether the influence data influences the operation of the robot and the stability of power supply, further ensures the operation safety and the control effect of the robot, and the specific disturbance supervision analysis process is as follows:
acquiring a line risk value of an internal line of the robot within a time threshold, wherein the line risk value represents a product value obtained by carrying out data normalization processing on a part of the running temperature of the line exceeding a stored preset running temperature and an average resistance value of a line port, comparing the line risk value with the stored preset line risk value, and if the line risk value is larger than the preset line risk value, marking a part of the line risk value larger than the preset line risk value as a line abnormal value XY, wherein the larger the value of the line abnormal value XY is, the larger the robot out-of-control risk is;
acquiring a delay risk value YF of an internal electrical element of the robot within a time threshold, wherein the delay risk value represents a product value obtained by carrying out data normalization processing on a part of the internal electrical element of the robot, the operation resistance of which is larger than a stored preset operation resistance threshold, and an internal environment temperature value of the robot, and the larger the value of the delay risk value YF is, the larger the influence risk on the action execution of the robot is, so that the control effect of the robot is reduced;
according to the formulaObtaining an interference evaluation coefficient, wherein a1 and a2 are preset scale factor coefficients of a line abnormal value and a delay risk value respectively, the scale factor coefficients are used for correcting deviation of various parameters in a formula calculation process, so that calculation results are more accurate, a1 and a2 are positive numbers larger than zero, a3 is a preset fault-tolerant factor coefficient, the value is 1.449, R is the interference evaluation coefficient, the interference evaluation coefficient R is sent to an execution performance unit, and meanwhile, the interference evaluation coefficient R is compared with a preset interference evaluation coefficient threshold value recorded and stored in the interference evaluation coefficient R:
if the interference evaluation coefficient R is smaller than a preset interference evaluation coefficient threshold value, no signal is generated;
and when the interference evaluation coefficients R are larger than or equal to the preset interference evaluation coefficient threshold, an interference signal is generated and sent to the early warning display unit, and after the early warning display unit receives the interference signal, preset early warning characters corresponding to the interference signal are displayed on the display panel 4 immediately, so that operators are reminded to reasonably manage and control the internal circuits and the electrical elements of the robot, the control influence degree on the robot is reduced, and the control sensitivity of the robot is improved.
Example 3:
the execution performance unit immediately acquires state data of the driving motor after receiving the interference evaluation coefficient R, wherein the state data comprises a rotating shaft friction value and a motor controller temperature value inside the driving motor, and performs feedback analysis on the state data to judge whether the driving motor normally runs or not so as to ensure the execution performance of the robot, and the specific execution feedback analysis process is as follows:
acquiring a rotating shaft friction value in a battery in each sub-time node, establishing a rectangular coordinate system by taking time as an X axis and taking the rotating shaft friction value as a Y axis, drawing a rotating shaft friction value curve in a dot drawing mode, drawing a preset rotating shaft friction value range value curve in the coordinate system, acquiring a ratio of a length value of a line segment of the rotating shaft friction value curve in the preset rotating shaft friction value range value curve to the total length of the line segment of the rotating shaft friction value curve from the coordinate system, and marking the ratio as a safety circumference value, wherein the reference number is AY;
acquiring a temperature value of a motor controller in a battery in each sub-time node, constructing a set B of the temperature value of the motor controller, acquiring an average value and a discrete coefficient of the set B, marking a product value obtained by carrying out data normalization processing on the average value and the discrete coefficient of the set B as a risk multiplier value, and marking the risk multiplier value as FB, wherein the risk multiplier value FB is an influence parameter reflecting the rotation state of a rotating shaft;
according to the formulaGet performance evaluationEstimating coefficients, wherein f1, f2 and f3 are preset weight factor coefficients of risk multiplier value, interference estimation coefficient and safety circumference value respectively, f1, f2 and f3 are positive numbers larger than zero, f4 is a preset correction factor coefficient, the value is 2.261, Z is an execution performance estimation coefficient, the execution performance estimation coefficient Z is sent to an integration feedback unit, and meanwhile the execution performance estimation coefficient Z is compared with a preset execution performance estimation coefficient threshold value recorded and stored in the execution performance estimation coefficient Z:
if the ratio between the execution performance evaluation coefficient Z and the preset execution performance evaluation coefficient threshold is smaller than one, no signal is generated;
if the ratio between the execution performance evaluation coefficient Z and the preset execution performance evaluation coefficient threshold is greater than or equal to one, generating an abnormal signal, sending the abnormal signal to an early warning display unit, and immediately controlling an early warning lamp 5 to work after receiving the interference signal by the early warning display unit, so that the early warning lamp 5 flashes to remind an operator to maintain and manage the internal driving motor of the robot so as to ensure the operation safety of the driving end;
the integrated feedback unit immediately acquires execution data of the robot after receiving the execution performance evaluation coefficient Z, the execution data represent execution time of each execution action, and carries out-of-control risk evaluation analysis on the execution data, so as to judge whether the control effect of the robot meets the standard or not, so that control optimization processing is carried out timely, and the accuracy of an analysis result is improved by carrying out combined evaluation analysis from three angles of a power supply end, a driving end and an execution end, wherein the specific out-of-control risk evaluation analysis process is as follows:
acquiring the execution time length of each execution action of the robot in the time threshold, comparing the execution time length of each execution action with a stored preset execution time length threshold corresponding to the execution time length, acquiring the total number of the execution actions corresponding to the execution time length greater than the preset execution time length threshold if the execution time length is greater than the preset execution time length threshold, and marking the total number as an abnormal constant YC, wherein the larger the value of the abnormal constant YC is, the larger the risk of the runaway of the robot is;
simultaneously, a discharge span value and a floating risk value are called from the power supply risk unit, and the discharge span value and the floating risk value are respectively marked as FD and FF;
according to the formulaObtaining a runaway risk assessment coefficient, wherein alpha, beta, epsilon and eta are respectively abnormal constants, execution performance assessment coefficients, discharge span values and preset influence factor coefficients of a floating risk value, alpha, beta, epsilon and eta are positive numbers larger than zero, S is the runaway risk assessment coefficient, and the runaway risk assessment coefficient S is compared with a preset runaway risk assessment coefficient threshold value recorded and stored in the runaway risk assessment coefficient S:
if the out-of-control risk assessment coefficient S is smaller than a preset out-of-control risk assessment coefficient threshold value, generating a normal signal, and sending the normal signal to an early warning display unit, wherein the early warning display unit immediately controls the early warning lamp 5 to work after receiving the normal signal, so that the early warning lamp 5 is a green light, and the control condition of the robot is intuitively known;
if the out-of-control risk assessment coefficient S is greater than or equal to a preset out-of-control risk assessment coefficient threshold value, generating an out-of-control signal, and sending the out-of-control signal to an early warning display unit, wherein the early warning display unit immediately displays preset early warning characters corresponding to the out-of-control signal on a display panel 4 after receiving the out-of-control signal so as to remind an operator to conduct management and control optimization on the robot, so that the control effect and the operation safety of the robot are ensured;
in summary, the combined evaluation analysis is performed from three angles of the power supply end, the driving end and the execution end, and the analysis is performed by combining the interference evaluation coefficient R, so that the control effect and the operation safety of the robot are guaranteed, meanwhile, the accuracy of an analysis result is improved, namely, the operation risk supervision analysis is performed on the power supply data of the power supply end, so as to judge whether the internal battery of the robot is normal or not, so as to guarantee the normal operation and the control of the robot, the feedback analysis is performed on the state data of the driving end, so as to judge whether the driving motor is normal or not, so as to guarantee the execution performance of the robot, the out-of-control risk evaluation analysis is performed on the execution data of the execution end, so that the control effect of the robot is up to standard, so that the control optimization processing is performed in time, and the early warning is performed in an information feedback mode so as to remind operators of performing the control optimization on the robot, so as to guarantee the control effect and the operation safety of the robot, and in addition, the operation safety and the control safety of the robot are guaranteed by performing the interference supervision analysis on the influence data, so as to judge whether the operation, the power supply stability and the control efficiency of the robot are affected by the influence data.
The size of the threshold is set for ease of comparison, and regarding the size of the threshold, the number of cardinalities is set for each set of sample data depending on how many sample data are and the person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected.
The above formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and coefficients in the formulas are set by a person skilled in the art according to practical situations, and the above is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art is within the technical scope of the present invention, and the technical scheme and the inventive concept according to the present invention are equivalent to or changed and are all covered in the protection scope of the present invention.
Claims (6)
1. Child programming robot based on artificial intelligence, including supporting baseplate (1), its characterized in that, the last fixed surface of supporting baseplate (1) is connected with protection box (2), one side fixedly connected with mainboard face guard (3) of protection box (2), one side inside fixedly connected with display panel (4) of keeping away from protection box (2) of mainboard face guard (3), one side top fixedly connected with early warning lamp (5) that mainboard face guard (3) are close to display panel (4), both surfaces all rotate around supporting baseplate (1) are connected with driving roller (6), chain strip (7) have been cup jointed to the outside of driving roller (6), the inside of supporting baseplate (1) is provided with driving motor, and driving motor is connected with driving roller (6).
2. The control system of the juvenile programming robot based on artificial intelligence of claim 1, wherein a control platform, a data acquisition unit, a power supply risk unit, a disturbance control analysis unit, an execution performance unit, an integration feedback unit and an early warning display unit are arranged in the display panel (4);
when the control platform receives an execution program and an execution instruction, a management instruction is generated and sent to the data acquisition unit, the data acquisition unit immediately acquires power supply data and influence data of the robot after receiving the management instruction, the power supply data comprise discharge current and discharge rate of an internal battery, the influence data comprise a line risk value and a delay risk value of an electric element, the power supply data and the influence data are respectively sent to the power supply risk unit and the disturbance control analysis unit, the power supply risk unit immediately carries out operation risk supervision analysis on the power supply data after receiving the power supply data, the obtained risk signal is sent to the early warning display unit, and the early warning display unit immediately displays preset early warning characters corresponding to the risk signal on the display panel (4) after receiving the risk signal;
the disturbance control analysis unit immediately carries out disturbance supervision analysis on the influence data after receiving the influence data, sends the obtained disturbance evaluation coefficient R to the execution performance unit, sends the obtained disturbance signal to the early warning display unit, and immediately displays preset early warning characters corresponding to the disturbance signal on the display panel (4) after receiving the disturbance signal;
the execution performance unit immediately acquires state data of the driving motor after receiving the interference evaluation coefficient R, wherein the state data comprises a rotating shaft friction value and a motor controller temperature value inside the driving motor, performs feedback analysis on the state data, sends an obtained execution performance evaluation coefficient Z to the integrated feedback unit, and sends an obtained abnormal signal to the early warning display unit;
and the integrated feedback unit immediately acquires the execution data of the robot after receiving the execution performance evaluation coefficient Z, wherein the execution data represents the execution duration of each execution action, carries out runaway risk evaluation analysis on the execution data, and sends the obtained normal signal and the obtained runaway signal to the early warning display unit.
3. The control system of an artificial intelligence based juvenile programming robot of claim 2, wherein the operational risk supervisory analysis process of the power supply risk unit is as follows:
s1: collecting the duration of robot operation for a period of time, marking the duration as a time threshold, dividing the time threshold into i sub-time nodes, wherein i is a natural number larger than zero, acquiring the discharge rate of batteries in each sub-time node, constructing a set A of the discharge rate, acquiring a maximum subset and a minimum subset in the set A, and marking the difference value between the maximum subset and the minimum subset in the set A as a discharge span value;
s12: acquiring the discharge current of the battery in each sub-time node, acquiring the difference value between the discharge currents in the two connected sub-time nodes, marking the average value of the difference values between the discharge currents in the two connected sub-time nodes as a floating average value, comparing and analyzing the floating average value with a stored preset floating average value threshold value, and marking the ratio between the part of the floating average value larger than the preset floating average value threshold value and the preset floating average value threshold value as a floating risk value if the floating average value is larger than the preset floating average value threshold value;
s13: comparing the discharge span value and the floating risk value with a preset discharge span value threshold value and a preset floating risk value threshold value which are recorded and stored in the discharge span value and the floating risk value respectively, and analyzing the discharge span value and the floating risk value:
if the discharge span value is smaller than or equal to a preset discharge span value threshold value and the floating risk value is smaller than or equal to a preset floating risk value threshold value, no signal is generated;
and if the discharge span value is greater than a preset discharge span value threshold value or the floating risk value is greater than a preset floating risk value threshold value, generating a risk signal.
4. The control system of an artificial intelligence based juvenile programming robot of claim 2, wherein the disturbance supervisory analysis process of the disturbance control analysis unit is as follows:
SS1: acquiring a line risk value of an internal line of the robot within a time threshold, wherein the line risk value represents a product value obtained by carrying out data normalization processing on a part of the running temperature of the line exceeding a stored preset running temperature and an average resistance value of a line port, comparing the line risk value with the stored preset line risk value, and if the line risk value is larger than the preset line risk value, marking a part of the line risk value larger than the preset line risk value as a line abnormal value XY;
SS2: acquiring a delay risk value YF of an internal electrical element of the robot within a time threshold, wherein the delay risk value represents a product value obtained by carrying out data normalization processing on a part of the internal electrical element of the robot, the operation resistance of which is larger than a stored preset operation resistance threshold, and an internal environment temperature value of the robot;
SS3: according to the formulaObtaining an interference evaluation coefficient, wherein a1 and a2 are preset scale factor coefficients of a line abnormal value and a delay risk value respectively, a1 and a2 are positive numbers larger than zero, a3 is a preset fault tolerance factor coefficient, the value is 1.449, R is the interference evaluation coefficient, and meanwhile, the interference evaluation coefficient R is compared with a preset interference evaluation coefficient threshold value recorded and stored in the interference evaluation coefficient R:
if the interference evaluation coefficient R is smaller than a preset interference evaluation coefficient threshold value, no signal is generated;
and generating interference signals when the interference evaluation coefficients R are larger than or equal to a preset interference evaluation coefficient threshold value.
5. The control system of an artificial intelligence based juvenile programming robot of claim 2, wherein the execution feedback analysis process of the execution performance unit is as follows:
acquiring a rotating shaft friction value in a battery in each sub-time node, establishing a rectangular coordinate system by taking time as an X axis and taking the rotating shaft friction value as a Y axis, drawing a rotating shaft friction value curve in a dot drawing mode, drawing a preset rotating shaft friction value range value curve in the coordinate system, acquiring a ratio between the length value of a line segment of the rotating shaft friction value curve in the preset rotating shaft friction value range value curve and the total length of the line segment of the rotating shaft friction value curve from the coordinate system, and marking the ratio as a safety circumference value AY;
acquiring a temperature value of a motor controller in a battery in each sub-time node, constructing a set B of the temperature value of the motor controller, acquiring a mean value and a discrete coefficient of the set B, and marking a product value obtained by carrying out data normalization processing on the mean value and the discrete coefficient of the set B as a risk multiplier value FB;
obtaining an execution performance evaluation coefficient Z according to a formula, and comparing the execution performance evaluation coefficient Z with a preset execution performance evaluation coefficient threshold value recorded and stored in the execution performance evaluation coefficient Z:
if the ratio between the execution performance evaluation coefficient Z and the preset execution performance evaluation coefficient threshold is smaller than one, no signal is generated;
if the ratio between the execution performance evaluation coefficient Z and the preset execution performance evaluation coefficient threshold is greater than or equal to one, generating an abnormal signal.
6. The control system of an artificial intelligence based juvenile programming robot of claim 3, wherein the integrated feedback unit is run-away risk assessment analysis process as follows:
acquiring the execution time length of each execution action of the robot in the time threshold, comparing the execution time length of each execution action with a stored preset execution time length threshold corresponding to the execution time length, and if the execution time length is longer than the preset execution time length threshold, acquiring the total number of the execution actions corresponding to the execution time length longer than the preset execution time length threshold, and marking the total number as an abnormal constant YC;
simultaneously, a discharge span value and a floating risk value are called from the power supply risk unit, and the discharge span value and the floating risk value are respectively marked as FD and FF;
according to the formulaObtaining a runaway risk assessment coefficient, wherein alpha, beta, epsilon and eta are respectively abnormal constants, execution performance assessment coefficients, discharge span values and preset influence factor coefficients of a floating risk value, alpha, beta, epsilon and eta are positive numbers larger than zero, S is the runaway risk assessment coefficient, and the runaway risk assessment coefficient S is compared with a preset runaway risk assessment coefficient threshold value recorded and stored in the runaway risk assessment coefficient S:
if the runaway risk assessment coefficient S is smaller than a preset runaway risk assessment coefficient threshold value, generating a normal signal;
and if the runaway risk assessment coefficient S is greater than or equal to a preset runaway risk assessment coefficient threshold value, generating a runaway signal.
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