Unmanned network robotics is a new multidisciplinary field that involves many fields of computer networks, multi-agent systems, control theory, 5G and 6G Internet, computer security, and wireless quantum communications. Efficient conjugation of such technologies needs to design new data verification schemes for robotic agents using the advantages of quantum key distribution lines. For such schemes the joint use of known fuzzy logic parametrical -gates and discrete multiple-valued logic models simplifies the application of quantum quasi-random keys. Namely, the separate regulating parameter in -gates is the most convenient tool to use quantum keys in comparatively simple classical control and verification procedures that do not involve quantum logic gates.
Unmanned network robotics is a new multidisciplinary field that involves many fields of computer networks, multi-agent systems, control theory, 5G and 6G Internet, computer security, and wireless quantum communications. Efficient conjugation of such technologies needs to design new data verification schemes for robotic agents using the advantages of quantum key distribution lines. For such schemes the joint use of known fuzzy logic parametrical -gates and discrete multiple-valued logic models simplifies the application of quantum quasi-random keys. Namely, the separate regulating parameter in -gates is the most convenient tool to use quantum keys in comparatively simple classical control and verification procedures that do not involve quantum logic gates.
Quantum optics is regarded as the acknowledged method to provide network quantum keys distribution and in the future secure distributed quantum computing, but it should also provide cryptography protection for mobile robots and the Internet of Things (IoT). This task requires the design of new secret coding schemes, which can be also based on multiple-valued logic (MVL). However, this very specific logic model reveals new possibilities for the hierarchical data clustering of arbitrary data sets. The minimization of multiple-valued logic functions is proposed for the analysis of aggregated objects, which is possible for an arbitrary number of variables. In order to use all the useful properties of the multiple-valued logic, the heterogeneous network architecture is proposed, which includes three allocated levels of artificial intelligence (AI) logic modeling for discrete multiple-valued logic, Boolean logic, and fuzzy logic. Multiple-valued logic is regarded as the possible platform for additional secret coding, data aggregation, and communications, which are provided by the united high dimensional space for network addressing and the targeted control of robotic devices. Models of Boolean and fuzzy logic are regarded as separate logic levels in order to simplify the integration of various algorithms and provide control of additional data protection means for robotic agents.
The intersection of Quantum Technologies and Robotics Autonomy is explored in the present paper. The two areas are brought together in establishing an interdisciplinary interface that contributes to advancing the field of system autonomy, and pushes the engineering boundaries beyond the existing techniques. The present research adopts the experimental aspects of quantum entanglement and quantum cryptography, and integrates these established quantum capabilities into distributed robotic platforms, to explore the possibility of achieving increased autonomy for the control of multi-agent robotic systems engaged in cooperative tasks. Experimental quantum capabilities are realized by producing single photons (using spontaneous parametric down-conversion process), polarization of photons, detecting vertical and horizontal polarizations, and single photon detecting/counting. Specifically, such quantum aspects are implemented on network of classical agents, i.e., classical aerial and ground robots/unmanned systems. With respect to classical systems for robotic applications, leveraging quantum technology is expected to lead to guaranteed security, very fast control and communication, and unparalleled quantum capabilities such as entanglement and quantum superposition that will enable novel applications.
The intersection of Quantum Technologies and Robotics Autonomy is explored in the present paper. The two areas are brought together in establishing an interdisciplinary interface that contributes to advancing the field of system autonomy, and pushes the engineering boundaries beyond the existing techniques. The present research adopts the experimental aspects of quantum entanglement and quantum cryptography, and integrates these established quantum capabilities into distributed robotic platforms, to explore the possibility of achieving increased autonomy for the control of multi-agent robotic systems engaged in cooperative tasks. Experimental quantum capabilities are realized by producing single photons (using spontaneous parametric down-conversion process), polarization of photons, detecting vertical and horizontal polarizations, and single photon detecting/counting. Specifically, such quantum aspects are implemented on network of classical agents, i.e., classical aerial and ground robots/unmanned systems. With respect to classical systems for robotic applications, leveraging quantum technology is expected to lead to guaranteed security, very fast control and communication, and unparalleled quantum capabilities such as entanglement and quantum superposition that will enable novel applications.
This dissertation introduces a new type of quantum automata, their encoding and circuit realization. I concentrate on possible applications in robotics. Several methods and application of quantum automata and quantum circuit-based controllers for elementary robotic systems, with a focus on humanoid robot motion, emotion, and behavior generation are illustrated in detail. The research introduces several novel methodologies that bridge quantum computing principles with robotic control, aiming to overcome the limitations of classical deterministic and probabilistic approaches. The dissertation first presents a quantum-circuit-based framework for generating non-repetitive and expressive (e)motions in a humanoid robot actor, using superposition and entanglement to produce families of synchronized yet probabilistic behaviors. It then introduces a flowchart-based synthesis method for quantum automata using one-hot encoding, which significantly reduces quantum circuit cost by leveraging EXOR-based logic and restricting gate sets to NOT, CNOT, and Toffoli gates. Finally, the work expands into ternary quantum logic, developing hybrid quantum finite automata (QFA) using Chrestenson-family gates and uniformization ternary quantum gates, enabling more efficient pattern and language recognition with smaller state spaces. The key contributions of this dissertation are multifold. First, it presents the first practical implementation of a quantum-controlled humanoid robot for theatrical performance, demonstrating visually distinct, expressive, and entertaining behaviors that extend beyond the capabilities of classical control systems. Second, it introduces a direct synthesis methodology for quantum sequential circuits derived from high-level flowcharts, achieving up to a 95% reduction in quantum cost compared to existing design approaches. Third, the dissertation develops the generalized hybrid quantum finite automata (GHQFA), integrating ternary quantum logic with classical automata to enable complex pattern recognition and robotic gesture interpretation while requiring minimal quantum cost. Although the illustrative example of a robot car simulated in the CoppeliaSim environment is very simple based only on Chrestenson gates, the integration of all methods proposed herein establishes a foundation for controlling highly expressive humanoid robotic systems. Furthermore, the proposed models can be applied to real-world robotic tasks, including gesture recognition, motion synthesis, and adaptive behavior generation, with validation through both physical robotic performances and simulation studies. Finally, this work introduces an r-of-n encoding method that can enable to encode large machines for quantum circuits and can be integrated with the entanglement and superposition methods presented in this dissertation. This dissertation lays the groundwork for scalable and practical quantum-robotic systems, offering a pathway toward more intelligent, adaptive, and engaging robotic agents through quantum-enhanced control architectures.
A quantum network may be realized by the entanglement of particles communicated by qubits between quantum computers, where the entangled photons of light are transferred for communication purposes. This technology has been proven to be feasible experimentally through free-space distribution of entangled photon pairs. Sending photons of light through nonlinear crystals produces correlated photon pairs, by splitting each photon into two half particles with each particle having the same level of energy, which results in entangled pairs. This entanglement is represented by photons, having both either horizontal or vertical polarization. This paper investigates collaborative robotic tasks of unmanned systems in a network where the agents are entangled. For instance, a leader robot sends two identical photons (e.g. with vertical polarization) to two follower robots/autonomous vehicles to communicate information about various tasks such as swarm, formation, trajectory tracking, path following and collaborative tasks. The potential advantages of quantum cooperation of robotic agents is the speed of the process, the ability to achieve security with immunity against cyberattacks, and fault tolerance, through entanglement. If a Quantum Network is implemented in a robotic application, it would present an effective solution; for example, for a group of unmanned systems working securely together. An analytical basis of such systems is investigated in this paper, and the formulation of quantum cooperation of unmanned systems is presented and discussed. The concept of experimental quantum entanglement, as well as quantum cryptography (QC), for robotics applications is presented.
A clever choice and design of gate sets can reduce the depth of a quantum circuit, and can improve the quality of the solution one obtains from a quantum algorithm. This is especially important for near-term quantum computers that suffer from various sources of error that propagate with the circuit depth. Parametrized gates in particular have found use in both near-term algorithms and circuit compilation. The one- and two-qubit versions of these gates have been demonstrated on various computing architectures. The neutral-atom platform has the capability to implement native N-qubit gates (for $N\ensuremath{\ge}2$). However, one needs to first find the control functions that implement these gates on the hardware. We study the numerical optimization of neural networks towards obtaining families of controls---laser pulses to excite an atom to Rydberg states---that implement phase gates with one and two controls, the C1P and C2P gates, respectively, on neutral-atom hardware. The pulses we obtain have a duration significantly shorter than the loss time scale, set by decay from the Rydberg state. In addition, they do not require single-site addressability and are smooth. Hence, we expect our gates to have immediate benefits for quantum algorithms implemented on current neutral-atom hardware.