AI self-adaptive combat robot system based on quantum nuclear fusion driving and control method of AI self-adaptive combat robot system

Abstract

The invention provides an AI self-adaptive combat robot system based on quantum nuclear fusion driving and a control method of the AI self-adaptive combat robot system, and belongs to the technical field of cross of artificial intelligence and quantum physics. The technical problems that in the prior art, energy efficiency is low, intelligent decision is lagged, and weapon system response is slow are solved, the system comprises a quantum nuclear fusion energy module, a micro black hole energy reactor is achieved through quantum gravitation constraint, the energy density reaches 1020 W / m < 3 >, and ultrahigh-speed maneuvering and weapon energy charging are supported; the quantum AI decision center is used for realizing 0.1 second-level dynamic modeling and tactical optimization of a battlefield environment based on a neural network processor of superconducting quantum bits; according to the quantum state weapon system, the quantum tunneling effect is used for controlling nanometer insect groups, and a reconfigurable attack form is formed.

Description

Technical Field

[0001] The present invention belongs to the cross - technical field of artificial intelligence and quantum physics, and specifically relates to an AI adaptive combat robot system driven by quantum nuclear fusion and its control method. Background Art

[0002] The energy supply and performance of traditional combat robots face many bottlenecks; from the perspective of energy, conventional energy sources such as chemical batteries and fuels have low energy density and cannot meet the requirements of long - time and high - intensity operations of combat robots; frequent energy replenishment not only affects the combat efficiency but also poses great risks in complex and dangerous battlefield environments; at the same time, traditional energy sources are inefficient in the energy conversion process, resulting in a large amount of energy waste and restricting the endurance and functional expansion of combat robots.

[0003] In terms of decision - making and control, the decision - making system of existing combat robots relies on classical computing architectures and has a slow speed in processing complex battlefield data; in the face of rapidly changing battlefield situations, such as the rapid movement of the enemy and the simultaneous emergence of multiple weapon threats, the problem of decision - making delay is prominent, and it is difficult to quickly make accurate and effective response strategies, resulting in a lag in the reaction of combat robots during combat, missing opportunities for battle or being unable to effectively avoid danger; in addition, the attack modes of traditional weapon systems are single and the switching speed is slow, and it is difficult to flexibly adjust the attack mode according to the actual battlefield situation. When facing diverse combat tasks and complex enemy defense systems, the combat effectiveness is greatly reduced.

[0004] To break through the above - mentioned dilemmas, the present invention proposes an AI adaptive combat robot system driven by quantum nuclear fusion and its control method; this solution utilizes the ultra - high energy density generated by quantum nuclear fusion to generate a micro - black hole reactor through quantum gravitational confinement, and the energy density can reach ≥1×10 20 W / m 3 , providing a powerful and stable energy supply for combat robots, greatly enhancing the endurance, reducing the energy replenishment requirements, and reducing the combat risks.

[0005] The quantum AI decision - making center is equipped with a superconducting quantum bit processor and runs a hybrid quantum - classical algorithm. The decision - making delay is ≤10ms, and it can process 10 6 pieces of battlefield data per second in high - speed parallel, greatly improving the processing speed and decision - making efficiency of complex battlefield data, enabling combat robots to quickly respond to battlefield changes and timely adjust combat strategies; the quantum - state weapon system manipulates nano - swarms with special nanostructures by means of the quantum tunneling effect, and the attack mode switching time is ≤5ms, with fast and flexible attack capabilities. It can quickly switch attack modes according to different combat scenarios and targets, significantly enhancing the combat effectiveness of combat robots, thus effectively solving the problems in multiple aspects such as energy, decision - making, and weapon systems existing in existing combat robots. Summary of the Invention

[0006] The purpose of the present invention is to provide an AI adaptive combat robot system driven by quantum nuclear fusion and its control method, aiming to solve the problem in the prior art that the decision-making system of existing combat robots relies on classical computing architectures, has a slow speed in processing complex battlefield data, and when facing rapidly changing battlefield situations, such as the rapid movement of the enemy and the simultaneous emergence of multiple weapon threats, the decision-making delay is prominent, making it difficult to quickly make accurate and effective response strategies, resulting in the combat robot lagging in combat, missing opportunities or being unable to effectively avoid dangers.

[0007] To achieve the above purpose, the present invention provides the following technical solutions:

[0008] An AI adaptive combat robot system driven by quantum nuclear fusion, characterized by comprising:

[0009] - A quantum nuclear fusion energy module that generates a micro black hole reactor through quantum gravitational confinement, with an energy density ≥ 1×10 20 W / m 3 ;

[0010] - A quantum AI decision-making center containing a superconducting quantum bit processor, running a hybrid quantum-classical algorithm, with a decision-making delay ≤ 10 ms;

[0011] - A quantum state weapon system that uses the quantum tunneling effect to control a swarm of nano-worms, with an attack mode switching time ≤ 5 ms.

[0012] As a preferred solution of the present invention, the quantum nuclear fusion energy module uses a niobium-titanium superconducting coil (critical current density ≥ 5×10 6 A / m 2 ), with a magnetic field strength ≥ 20 T.

[0013] As a preferred solution of the present invention, the quantum bit gate fidelity of the quantum AI decision-making center ≥ 99.99%, supporting parallel processing of 10 6 pieces of battlefield data per second.

[0014] As a preferred solution of the present invention, the swarm of nano-worms contains iron-based nanoparticles (particle size 50 ± 5 nm), with graphene quantum dots (thickness 2 nm) coated on the surface.

[0015] Compared with the prior art, the beneficial effects of the present invention are:

[0016] 1. In this solution, the present invention generates a micro black hole reactor through quantum gravitational confinement, with an energy density as high as ≥ 1×10 20 W / m 3, which represents a qualitative leap compared to traditional energy sources. It uses a niobium-titanium superconducting coil (critical current density ≥ 5×10 6 A / m 2 ) to generate a magnetic field with a magnetic field strength ≥ 20T, maintaining the stable progress of the quantum nuclear fusion reaction and providing a powerful and stable energy supply for the entire combat robot system. This measure effectively solves the problems of low energy density and poor endurance of traditional energy sources, greatly improves the endurance of combat robots, reduces the demand for energy replenishment, and reduces the risk of energy replenishment in complex battlefield environments, enabling combat robots to execute combat tasks for a long time and with high intensity.

[0017] 2. In this solution, the quantum AI decision-making center is equipped with a superconducting quantum bit processor, running a hybrid quantum-classical algorithm, with a decision-making delay ≤ 10ms, a quantum bit gate fidelity ≥ 99.99%, and supporting parallel processing of 10 6 pieces of battlefield data per second. These characteristics enable the decision-making center to quickly process various complex data from the battlefield, significantly improving the processing speed and decision-making efficiency of complex battlefield data. Facing the rapidly changing battlefield situation, combat robots can quickly respond, timely adjust their combat strategies, effectively solve the problems of prominent decision-making delay in traditional decision-making systems and difficulty in making accurate and effective response strategies, improve the reaction speed and decision-making accuracy of combat robots in combat, and enhance their combat effectiveness and survival ability.

[0018] 3. In this solution, the quantum state weapon system uses the quantum tunneling effect to control a swarm of nano-robots containing iron-based nanoparticles (particle size 50 ± 5nm) and surface-coated graphene quantum dots (thickness 2nm), and the attack mode switching time ≤ 5ms. This special nanostructure endows the swarm of nano-robots with unique physical and chemical properties, enabling them to have a fast and flexible attack ability. The weapon system can quickly switch the attack mode according to different combat scenarios and targets, effectively solving the problems of single attack mode and slow switching speed of traditional weapon systems, significantly enhancing the combat effectiveness of combat robots, and improving their adaptability to diverse combat tasks and the ability to break through complex enemy defense systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0020] Figure 1 is the overall system architecture and energy supply flowchart of the present invention;

[0021] Figure 2 is the working flowchart of the quantum AI decision-making center of the present invention;

[0022] Figure 3This is the attack flow chart of the quantum state weapon system of the present invention. Detailed implementation mode

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0024] Embodiment 1

[0025] Please refer to Figures 1 - 3 , the present invention provides the following technical solutions:

[0026] An AI adaptive combat robot system based on quantum nuclear fusion drive, characterized in that it includes:

[0027] - A quantum nuclear fusion energy module that generates a micro black hole reactor through quantum gravitational confinement, with an energy density ≥ 1×10 20 W / m 3 ;

[0028] - A quantum AI decision-making center, including a superconducting quantum bit processor, running a hybrid quantum-classical algorithm, with a decision-making delay ≤ 10 ms;

[0029] - A quantum state weapon system that uses the quantum tunneling effect to control a nanobot swarm, with an attack mode switching time ≤ 5 ms.

[0030] In a specific embodiment of the present invention, the quantum nuclear fusion energy module generates a micro black hole reactor through quantum gravitational confinement, and its ultra-high energy density (≥ 1×10 20 W / m 3 ) provides a strong and stable energy supply for the entire combat robot system. Using a niobium-titanium superconducting coil (critical current density ≥ 5×10 6 A / m 2 ), a magnetic field with a magnetic field strength ≥ 20 T can be generated, and this magnetic field environment helps to maintain the stable progress of the quantum nuclear fusion reaction.

[0031] Provide continuous electrical energy for the quantum AI decision-making center to ensure that the superconducting quantum bit processor can stably run the hybrid quantum-classical algorithm. Since the decision-making delay requirement is ≤ 10 ms, a stable energy supply is required to support the high-speed operation of the processor, and the stable energy provided by the energy module ensures the fast response ability of the decision-making center.

[0032] Provide energy for the quantum state weapon system to support its manipulation of the nano swarm using the quantum tunneling effect. The manipulation of the nano swarm requires a large amount of energy, especially when the attack mode switching time ≤ 5 ms, which poses high requirements for the rapid supply and stability of energy. The nuclear fusion energy module can meet this demand.

[0033] For details, please refer to Figures 1 - 3 , the quantum nuclear fusion energy module uses a niobium-titanium superconducting coil (critical current density ≥ 5×10 6 A / m 2 ), and the magnetic field strength ≥ 20 T.

[0034] In this embodiment: The quantum AI decision-making center includes a superconducting quantum bit processor with a quantum bit gate fidelity ≥ 99.99%, supporting parallel processing of 10 6 pieces of battlefield data per second. This enables the decision-making center to quickly process various complex data from the battlefield, such as the positions of the enemy, the states of weapons, terrain information, etc.

[0035] Based on the processed battlefield data, the decision-making center makes decisions quickly and sends instructions to the quantum state weapon system. For example, when detecting an enemy target, the decision-making center can make an attack decision within ≤ 10 ms and send an attack instruction to the weapon system. The weapon system switches the attack mode within ≤ 5 ms according to the instruction and manipulates the nano swarm to attack.

[0036] The decision-making center will also make a reasonable energy distribution and usage plan according to the energy state of the energy module. When the energy supply is sufficient, the decision-making center can allow the weapon system and other modules to operate more efficiently; when the energy supply fluctuates or is insufficient, the decision-making center will adjust the operation strategy of the system to give priority to ensuring the operation of key functions.

[0037] For details, please refer to Figures 1 - 3 , the quantum bit gate fidelity of the quantum AI decision-making center ≥ 99.99%, supporting parallel processing of 10 6 pieces of battlefield data per second.

[0038] In this embodiment: The quantum state weapon system manipulates the nano swarm using the quantum tunneling effect. The nano swarm contains iron-based nanoparticles (particle size 50 ± 5 nm) with graphene quantum dots (thickness 2 nm) coated on the surface. This special nanostructure enables the nano swarm to have unique physical and chemical properties and be able to execute attack tasks more effectively.

[0039] For details, please refer to Figures 1 - 3 , the nano swarm contains iron-based nanoparticles (particle size 50 ± 5 nm) with graphene quantum dots (thickness 2 nm) coated on the surface.

[0040] In this embodiment: The weapon system receives instructions from the quantum AI decision-making center and quickly switches the attack mode according to the instructions. During the attack, the weapon system will real-time feedback the attack status and effects to the decision-making center, and the decision-making center will further adjust the attack strategy according to the feedback information to achieve a more accurate and efficient attack.

[0041] The operation of the weapon system depends on the energy provided by the quantum nuclear fusion energy module. The continuous and stable energy supply of the energy module ensures that the weapon system can be in a standby and attack state at any time, and can quickly switch the attack mode to meet the combat requirements.

[0042] Finally, it should be noted that: The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An AI adaptive combat robot system driven by quantum nuclear fusion, characterized in that: include: -Quantum nuclear fusion energy module, generates a micro black hole reactor through quantum gravitational confinement, with an energy density of ≥1×10 2 0W / m 3 ; -Quantum AI decision-making center, including superconducting qubit processor, running hybrid quantum-classical algorithm, with decision delay ≤ 10ms; -Quantum weapon system, using quantum tunneling effect to control nano-insect swarms, attack mode switching time ≤ 5ms.

2. The system according to claim 1, characterized in that The quantum nuclear fusion energy module adopts niobium-titanium superconducting coils (critical current density ≥ 5×10 6 A / m 2 ), magnetic field strength ≥20T.

3. The system according to claim 1, characterized in that The quantum AI decision-making center has a quantum bit gate fidelity of ≥ 99.99% and supports parallel processing of 10 6 Battlefield data / second.

4. The system according to claim 1, characterized in that The nanoworm swarm comprises iron-based nanoparticles (particle size 50±5nm) with graphene quantum dots (thickness 2nm) coated on the surface.

Images