Innovative research on the application of TIRZ theory to multi-mode UAVs

According to the current development of Unmanned Aerial Vehicles (UAVs), it can be known that there are no cases where underwater drones and aerial drones are used in parallel. They are all affected by air and water resistance and are easily disturbed in various environments, making it difficult to move effectively. This research uses TRIZ theory to create a multi-modal unmanned vehicle to innovate and improve the existing situation. The type of equipment produced through this research can effectively move in the air, land, and water. The scope includes TRIZ theory, bionic technology, multi-modal innovative design, research, and application of UAV innovation, and monitoring the improvement of its operational resistance through fluid analysis. The output of this research will effectively promote the development of Multi-mode UAVs and improve the problems of existing UAVs.


Introduction 1.Multi-mode UAVs research background
Multi-modal UAV is an emerging research field with many application prospects and development potential.It can simultaneously face different environmental problems for transportation and operation, but many issues and parts must be solved.Currently, the most common Multi-mode UAVs face two significant issues: integration and perception.The integration problem is because Multi-mode UAVs need to integrate different modes and systems, such as air, ground and underwater.These systems must be integrated at the design and control levels, so a high degree of design analysis and structural thinking is required.The perception problem is that Multi-mode UAVs need to perceive and recognize different environments.For example, the air mode must sense and act on the surrounding weather, wind speed, height, etc.In contrast, the underwater method must be aware of the surrounding water quality and flow, water depth, etc., for perception and action.Given this, this study proposes corresponding innovative research and solutions based on the above two problems.

Algorithm for inventive-problem solving (ARIZ)
ARIZ was initially proposed by Ahshuller in 1956.After several revisions and revisions, a relatively complete system was formed.ARIZ is a complete algorithm for solving invention problems.It is the most robust and powerful tool in TRIZ innovation theory, integrating most of the ideas and tools in TRIZ theory and achieving innovative inventions and research outputs through systematic structures and processes.The reference comes from Clément [1].ARIZ contains three basic elements, including a series of steps, simplifying problems and controlling thinking through procedures, and applying Table 1.ARIZ 85-AS solution method (This study summarizes).

Step
Step contents Way 1 Determine the problem Identify problems and describe their nature and characteristics, and determine their causes.

Collect information
Gather all available information about the problem, including technical characteristics, technical limitations, existing solutions, relevant knowledge areas, and experience.Level 3: Find patterns in existing solutions.
Level 4: Find similar solutions from other systems.
Level 5: discover innovative solutions to problems and further optimize them.
Select the best solution The ARIZ innovation algorithm will include the six steps described in the table, of which critical applications will be modified and innovated at the fifth step level [3].Steps 1 to 4 are to collect information from problem confirmation and clarification and define engineering contradictions in modifying problems.That is the problem's core, and the contradiction category's definition conforms to the contradiction matrix in the TRIZ tool.This research is organized as shown in Table 2.After repeated confirmation, define the desired target state and problem-solving points.The fifth step is to innovate solutions through hierarchical problem-solving extended by the contradiction matrix.The hierarchical analysis process is shown in Table 3.It will be further optimized to the best state, and finally, the feasibility and analysis of the scheme will be confirmed.In the above table, the feature to be improved is the I part of the vertical axis, which will be listed using the 39-image contradiction matrix.The horizontal axis to which J belongs is the part that avoids the deterioration of the contradiction.Based on this contradictory comparison, in the system tools disclosed by TRIZ, an innovative solution will be sought to eliminate 40 development principles.Various creative steps are extended through innovative solutions to produce more competitive UAV designs.AHP was proposed by Thomas, L. Saaty, a professor at the University of Pittsburgh in the United States in 1971, when he was engaged in research on contingency planning for the US Department of Defense [4] It mainly assists decision-making through multiple evaluation criteria in the face of various uncertain results.This study found that although ARIZ has high innovative breakthrough thinking assistance, it is prone to produce too many solutions, and AHP can help this system to approach perfect solutions, ARIZ will produce countless inventive solutions by comparing the fundamental contradiction of the problem and the technical contradiction.At this time, through the hierarchical analysis, AHP can have objective, innovative thinking and adequate decision-making definitions.AHP hierarchical analysis can more effectively solve the judgment of complex problems in the field of decision-making with multi-objective or multi-criteria.Through this study, we understand that ARIZ mainly lies in the various solutions of innovative systematic inventions.Applying AHP can more effectively help this study achieve the accuracy of decision-making and judgment.The research of R.Y.M. Li in the literature shows that the AHP hierarchical analysis can effectively evaluate the consistency and make the most objective decision-making for the study [5].After the matrix is established, the vector value must be calculated next.To find the weight, α in the formula is the numerical value representing the weight in the paired comparison matrix, and most studies use 1/9, 1/8,． ． ．, 1/2, 1, 2, ． ． ．, 8, 9 to do weight analysis, n is the final number of the content of the questionnaire, in order to identify the decision value of the problem.the formula is as follows:

ICPMMT-2023
Generally speaking, when the AHP method calculates the vector value, it uses the row mentioned above vector average value normalization method to sum.
It can be known from the formula that before calculating C.I., the value of λ must be obtained; therefore, using the weight w obtained above, we first calculate the consistency vector and use the symbol ν to get the value of λ.The formula is: After obtaining the consistency vector, calculate the arithmetic mean of its ν value to get the λ value, and its formula is: Finally, the C.I. value can be obtained by substituting its λ value; C.I.=0 means that the judgments before and after are entirely consistent.If both are in the case of R.I.<0.1, it can be regarded as having better consistency, which also means that the research output has a specific contribution Value; through the hierarchical analysis of AHP used in this study, it can effectively improve the research output.

Research purpose
The above-mentioned multi-modal background research: the integration problem and the perception problem.This research uses the ARIZ tool in TRIZ to carry out systematic, innovative research and development.However, too many invention solutions ARIZ produces require hierarchical and objective evaluations.In this study, AHP level analysis is combined with ARIZ's five levels of verification to seek the best and most objective innovations.Finally, the innovativeness of the output multi-modal UAV is verified through flow field analysis.In addition to creating innovative research in this way, it provides academic and industrial references to promote the diversified development and application of Multi-mode UAVs.The research process architecture of Multi-mode UAVs this research is summarized in Figure 1.From the first stage to the fourth stage, we will conduct data collection analysis and in-depth discussion from the existing multi-modal drones, and based on this background, the contradictory content in the ARIZ tool is generated to formulate the best solution and the solution for the multi-modal UAV that is expected to be produced.In the fifth stage, the five levels of ARIZ will be combined with the contradiction matrix tool to find a complete solution, and the invention tool will be produced from the ARIZ system tool.This is further optimized, and finally, the feasibility of the research is confirmed through AHP hierarchical analysis and fluid analysis.

ARIZ innovative process application 2.2.1. Existing problems of multi-rotor unmanned aircraft
It can be seen from the research background information that Multi-mode UAVs are one of the research projects that have attracted attention in the past two years.There are currently two key objectives to be resolved.This research is listed as follows: Integration issues: Multi-mode UAVs must integrate different modes and systems, such as air, ground and underwater, etc.These systems must be integrated at the design and control levels, so a high degree of technical and planning design capabilities is required.Perception issues: Multi-mode UAVs need to sense and recognize different environments.For example, the air mode needs to sense the surrounding weather, wind speed, height, etc.In contrast, the underwater method must perceive the surrounding water quality, water flow, and depth.After sorting out the above two major issues, the current multi-modal UAV research focus will be collected through the following steps to confirm this study's final research direction and solution goal.

Collect the characteristics and related applications of multi-modal drones
Currently, the research of Multi-mode UAVs will mainly optimize and integrate five aspects: hardware system, software system, control system, communication system, and integrated system.Different types of application scenarios and requirements require various system analyses.The optimization mentioned above content can also help the UAV's optimization direction and improve the technology's overall performance and reliability.In the research literature, it can be seen that optimizing the software system [6] uses deep learning to improve the security problems faced by drones, as well as improving the way UAVs use different propulsion systems to optimize the control system in the air [7], even through the use of Multi-mode UAVs in flight to realize the communication system optimization of the positioning system [8], all are the current optimization targets.However, the hardware problems and over-design of multi-modal drones are undeveloped and research targets.So this research will improve and optimize the potential issues of the hardware system and integrated system based on this one.

Identifying paradoxical problems in multi-mode UAVs
In this study, through the above two processes, to improve the existing integration and perception problems, it is necessary to optimize the hardware and integration system of the current multi-modal UAV to create a UAV that can adapt to multiple fields.Through ARIZ's contradiction matrix tool, the contradictory goal of this research is proposed.ARIZ's innovation system has a principle that once we optimize a specific function or procedure, another part of the function and system may be weakened.Therefore, by listing the contradiction matrix, we can focus more on the evolution of innovation.The contradiction matrix formulated in this research is listed in Table 4 below. of IFR is to achieve the most significant degree of progress with a slight change in the system.The formula for this quantitative description is: The ideal IFR research compiled in this study is shown in Table 4 below.It can effectively combine the shape of the carrier with the design that can face both air and water From the obstacles and functions to be solved in the evolution of Multi-mode UAVs listed in Table 5, the quantitative description formula that incorporates it into the IFR is as follows: Ideal degree ∑ Movable power hardware and form factor in various environments ∑ Redundant mobile tool design excessive installations In the IFR description form of the ideal degree, the ideal degree is the evolution of gradual thinking and innovation for the content of this research.The best perfect degree in the innovation speech of multimodal drones is the best solution for the integration and appearance of the carrier that can move in various environments and the function of multi-environment survival.What needs to be reduced in this research is the design of redundant mobile tools and the problem of too many devices.The presentation through IFR analysis can better condense the best development of the research direction.

Application of the five levels of ARIZ 85-AS 2.2.5.1. Determine the underlying contradiction of the problem
The problems that need to be improved from the contradiction matrix in

Identify technical contradictions to resolve the problem
According to the ideal development of IFR, to improve the part of the integrated system, this research uses 35.Adaptability or versatility among the 40 principles for research and development, and 13.Stability for the development and application of the hardware system.

Finding patterns for existing solutions
Through the above steps, 2.2.5.1 and 2.2.5.2 integrate the potentially avoidable and contradictory content to be improved in the contradiction matrix.This way, the inventive tool embedded in the TRIZ contradiction matrix solves the problem.The resulting TRIZ 40 invention principles are shown in Table 5 below, and the application can be seen in the information demonstrated in Table 2.It can be seen from Table 5 that in the corresponding improvement part and the avoidance of deterioration part, the corresponding invention principles are generated in the TRIZ system, it is a developmental solution invention principle for multi-mode UAVs that currently intend to operate in multiple environments.

Find similar solutions from other systems
From the two issues listed in Table 3 to be improved in this study, in contrast to Table 6, the invention principles generated through the TRIZ system, in this way, the feasible solutions are extended, and the possible solutions are summarized as shown in Table 7.It can be seen from Table 5 that after setting the two goals for innovation in this study, according to the above-mentioned ARIZ 85-AS process, the summary analysis needs to summarize the inventions that can be innovated in the system into the four points in table.Based on these four points, it can be seen that the innovative and modifiable goals of Multi-mode UAVs are all innovative applications that can create multi-modal responses to environmental problems.

Unearth innovative solutions to problems and further optimize them
According to the innovative research viewpoints described in Table 7, further excavate and deepen the visible revision development direction, and integrate them as shown in Table 8 below.To further deepen this research, organize the innovative content as the four points in the above table, it can achieve effective innovation and development for existing Multi-mode UAVs that must face different fields and different operations.This study will follow the above four points to carry out AHP hierarchical analysis to achieve objective and in-depth decision-making and judgment development and application.

AHP combined with ARIZ level analysis 2.2.6.1. Definition of the problem
The background of this study is that Multi-mode UAVs are located in different environments and can effectively operate and move.Therefore, it is necessary to take into account the relevant factors of the environment, the existing problems of multi-mode drones, the issues of mobile devices, and the difficulties of minimized mechanical structures.Under the many constraints mentioned above, the entire research decision needs to be determined so to make the calculation process of AHP more precise.The goal of this research design is the "Development of Multi-mode UAVs capable of coping with air and water environments," and it is used for calculation evaluation.

Construct a hierarchical structure
This study focuses on decision-making.The main essential improvement and innovation factors are the four factors derived from ARIZ, which are "15: Dynamics", "28: Mechanics substitution", "35: Parameter changes", "31: Porous materials" The operable influencing system is 1.Integrated design, and 2. The hardware system draws a hierarchical structure diagram based on this condition, as shown in Figure 2.

Extensive investigation
The questionnaire is mainly divided into two stages.Table 9 explains the decision-making and selection keys of the four innovative solutions in the first stage, and Table 10 shows the second stage, which illustrates the impact conditions of the purposes mentioned above.PS：If the score is 9:1, it means that the experts believe that the Mechanics substitution improvement plan is better than Dynamics, and so on.The pairwise comparison matrix is calculated as follows: According to this table 10, it is inferred that the invention tends to decide where the system is biased.This table must be evaluated against the above four invention principles and used as an objective reference.

Verification of hierarchical consistency
First of all, we must first calculate the content of the questionnaire in the first stage.This questionnaire invites graduate students from the School of Engineering of Feng Chia University to conduct evaluations and provide professional assessment.The sample content is the average content of 20 people, so we get the following comparison matrix shown in Table 11 and calculate the total column value of the corresponding invention factor.The values in the matrix are then divided by the sum of each column to obtain the normalized values, as shown in Table 12 below.According to the formula (1) of the row vector average value standardization method, it can be known that the weight value of each factor can be obtained by summing up the columns and averaging them, as shown in Table 13 after the weights are calculated in this study, the issue of consistency needs to be considered, so the next step will be to figure the C.According to formula (2), I value to make sure that the value we calculated is a valid weight with consistency.According to the formula mentioned above, it can be seen that to obtain the C. I value, the consistency vector must be calculated first, such as formula (3), and the value of λ can be calculated before the C.I. value can be solved.Therefore, the consistency vector value of the research formula is as follows: It can be seen from Table 16 that the final weights are consistent, which means that the synchronization of the two systems is critical.Therefore, the best innovation solution finally obtained in this research is that both approaches must be innovative simultaneously.The breakthrough point of innovation is defined as Dynamics>Parameter changes>Mechanics substitution>Porous materials to make the final decision-making innovation stack.

The results of this study
This research uses ARIZ's innovation theory to derive the multi-modal UAV innovation structure.It considers the importance of structuring and simplifying the structure based on this standard, according to the comparison in the contradiction matrix, in the overall output, various resistance factors and the system of multi-modal moving methods must also be considered.
For the Dynamics and Parameter changes that are the key points of the invention, this research will produce a lightweight and integrated structure so that the existing multi-modal drones are no longer a combination of diverse and complicated tools but a systematic and structured integration.Figure 3 is the three views of the innovation of this research.Through the output of this research, the use of elliptical and circular structures allows the rotor to fly effectively and move on land, in addition, the last two points, Mechanics substitution and Porous materials, described in the structural improvement and invention principles, this research also applies the output of this aspect to the mobile device and thus forms the world's first multi-type mobile tool, which has three mobile functions of land, sea, and air, and uses various holes to achieve lightweight and resistance.The structure diagram is shown in Figure 4.

Innovation Points of multi-mode UAVs
The research output of 3.1 shows that the application under the ARIZ innovation theory has originality and systematic innovation.Through the above output results, the following innovations to solve existing problems are integrated.

Main structure against environmental resistance
It can be seen from the main structure that this study considers the modification of the overall unit structure based on the resistance of various environments, especially the pressure of wind flow and water resistance, as shown in Figure 5, and use the porous design to guide the flow of wind pressure and water pressure.In order to promote the main body to achieve the design of guiding the pressure to spread according to the appearance, the output of this research is to design the cutting resistance for the head shape of the body and design a circular arc at the tail to guide the flow state of the airflow and water flow in the same direction, as shown in Figure 6, thereby improving the efficiency of movement.From the above pictures 5 and 6, it can be seen that the design of the structure not only guides the flow, but also maximizes the resistance to wind resistance through various joints, as shown in Figure 7, it can be seen that it is used to guide the flow direction of resistance.In addition, in order to meet the diversion and portability of the device, this study also discarded redundant structures, and used the method of porosity to improve the overall performance.Finally, fluid analysis was used to verify the longitudinal effect.

Multi-modal mobile device integration.
The integrated system has always been an important problem to be solved for multi-modal drones, and even many multi-modal drones are listed as one of the key points to be improved, in this study, the innovative solution was deduced through the ARIZ innovation theory, and the design thinking was based on this, and finally a multi-circle structure of ellipse and circle was designed, as shown in Figure 8.The red wheel in the picture is a design that can travel on land and slow down the collision between the air and the sea, while the blue blade represents the rotor that combines the air and the sea, and achieves a synergistic application through the control of fluid, in order to be able to operate effectively without affecting the air pressure generated by flowing driving, the gray arc frame is designed to add fixed points to improve the strength and reduce the impact of excessive equipment on the operation of the airflow.The design of the elliptical wire frame makes the overall operation more efficient.

Multi-environment mobile design.
From the application of the two major innovations of 3.2.1 and 3.2.2, the integrated system and environmental perception system in the multi-modal UAV are solved, in order to promote him to deal with more multi-faceted environmental mobility problems, this study derived its design to able to move according to a single device, as shown in Figure 9, the four-axis model of this study combines the simulated models of four tires to complete this innovative structure, and based on this, it is finally introduced into fluid analysis to explore the visibility of the research results.

Fluid dynamics analysis
In this study, the COMSOL fluid analysis system is used to verify and confirm the main body.In order to ensure that the main body produced in this research can effectively move in various environments, the environments are respectively set in air and water, and explore the resistance state it faces in this environment.First of all, this research sets the moving speed 8 (m/s) of the general unmanned vehicle to about 30 (km/h), and it moves in the air, in order to confirm the state of the output of this research when it can move in the air or on land, and set the singlephase fluid in the laminar flow area governed by the Navier-Stokes equation one by one in the analysis software, the results are shown in Figure 10.It is the fluid simulation analysis of air movement based on the results of this research.The purpose of the analysis is to verify whether this output can be effectively moved in this environment, from the results, it can be seen that the results of this study can work well in the air and will not be affected by the viscosity in the air.As can be seen from the presentation results in the above figure, the impact on the subjects created in this research while maintaining the movement in the air, can almost guide the wind resistance to conduct flow from the four sides of the main body so that the main body can move effectively in the air without being affected.Based on this research and analysis, it can be seen that this product has the effective ability to move in the air in response to the multi-environment response of the multi-modal UAV, the environment is set to move in the water, and the moving speed setting is also set to 8 (m/s), which is about 30 (km/h), the operating fraction and set are compared with the above method, and the derived result is shown in Figure 11.The same reasoning proves that the output of this research can also work well in this environment under the condition of a large viscosity coefficient in water.Through the verification of fluid analysis, the multi-modal UAV in this study can effectively cope with various environments and move.According to the above analysis results, it can be seen that the output of this research is carried out by ARIZ in the TRIZ tool for innovation drills, the AHP hierarchical analysis convergence content is used for innovation evolution output, and the final output results are verified by fluid analysis, from the results, the multi-modal UAV integration problem and perception problem can be improved, and various environmental interferences in the movement can be reduced.

Conclusions
This research disassembles and innovates the two most common problems faced by multi-mode UAVs, integration problems and perception problems.Through systematic innovation steps and evolution, the new innovative research method combining ARIZ with AHP hierarchical analysis finally leads to the output results of this research.The innovative contributions of this study are summarized in the following key points, in the past, the design of multi-modal drones was to separate several devices to operate in the corresponding environment, this research improves the integrated system and creates a device that can move on land, sea and air.Moving in various environments has perceptual problems, so most of the devices that move in the air and move underwater are difficult to work with.In this study, the appearance structure of the hardware system is changed, so that the multi-mode UAVs can move effectively in various environments.the output results effectively improve the integrated system and hardware perception system of multi-modal unmanned vehicles.The innovative content of this research can effectively assist the development of reconnaissance aircraft and unmanned aerial vehicles, and can respond to more diverse environments for more development.It also makes a major breakthrough and design for the status quo of multi-modal unmanned aerial vehicles.

3 4 5 Five 2 :
Define contradictionsIdentify the contradiction in question, which is the core of the problem.Define ideal state Identify the desired state, which is the state where the end goal or solution should be.choose the technical contradictions to solve the problem.

Figure 1 .
Figure 1.The structure of this research.

Figure 2 .
Figure 2. Hierarchical structure diagram of this study.

Figure 3 .
Figure 3. Three views of the output of this research.

Figure 4 .
Figure 4. Structure of this study.3.2.Innovation Points of multi-mode UAVsThe research output of 3.1 shows that the application under the ARIZ innovation theory has originality and systematic innovation.Through the above output results, the following innovations to solve existing problems are integrated.

Table 2 .
Contradiction matrix example table (This study summarizes).

Table 3 .
ARIZ's analytical hierarchy process applied to AHP (This study summarizes).

Table 4 .
Engineering parameters in the contradiction matrix of this study.It can be seen from the above table that to improve the integrated system and hardware system; it is necessary to use the engineering parameters of the ARIZ contradiction matrix to find items that can be corrected and weakened and to evolve an executable research plan based on the above items.
2.2.4.Set ideal development from existing generalized problems.To avoid the defects of too divergent thinking and low innovation efficiency in traditional innovation methods such as trial and error and brainstorming, at the beginning of solving the problem, TRIZ's IFR puts aside various objective constraints, and this research will use TRIZ's IFR rule to set the ideal development state, and use this to draw up the perfect output of this research.The qualitative description

Table 5 .
Research IFR ideal innovation analysis table.Mobile devices in the air and in the water are different, and the resistance they receive is different The reason for this obstacle result?The design of the body is different from the accessories of the mobile carrier, and the way to deal with the environment is also different Conditions for such a barrier not to arise?
Table 3 include: 36.device complexity, 27.Reliability, 19.Moving parts consume energy, and 21.Motivation.Pointing to 36.device complexity, and 21.Motivation in this study, the two output results are that this study must think about the problem of avoiding deterioration.

Table 6 .
Contradictions arise in multi-modal UAV innovation research.

Table 7 .
Contradictions arise in multi-modal UAV innovation research.

Table 8 .
Contradictions arise in multi-modal UAV innovation research.

Table 9 .
The stage level comparison table.

Table 10 .
The second stage level comparison table.

Table 11 .
Invention factor calculation column summary table.

Table 12 .
Invention factor standardized pairwise comparison matrix table.