In the present work we propose a scheme to control the network of wheeled mobile robots using Quantum computing. This scheme provides a fast and efficient way to navigate a system of networked robots from one position to another using a PID Controllers. It is a well established fact that the robotic systems aredefined using Lagrangian dynamics and PID control is an efficient way to control the movement of robotic systems . In the present work we propose a framework to use Quantum Computers and Photic couplings among robots to form a consensus and move a the coupled robotic system from one place to another. We propose that all the computations must be carried out on quantum computers for efficient control and fast execution. We propose an algorithm that enables the proposed scheme. Numerical Simulations that show synchronized motion of coupled robots have been reported.
In the present work we propose a scheme to control the network of wheeled mobile robots using Quantum computing. This scheme provides a fast and efficient way to navigate a system of networked robots from one position to another using a PID Controllers. It is a well established fact that the robotic systems aredefined using Lagrangian dynamics and PID control is an efficient way to control the movement of robotic systems . In the present work we propose a framework to use Quantum Computers and Photic couplings among robots to form a consensus and move a the coupled robotic system from one place to another. We propose that all the computations must be carried out on quantum computers for efficient control and fast execution. We propose an algorithm that enables the proposed scheme. Numerical Simulations that show synchronized motion of coupled robots have been reported.
Quantum computing has garnered significant interest in robotics applications over the past few years. Demonstrating its superiority over traditional methods, it has shown many advantages in precision, rapid computation, and robustness for Manipulators and cell robots. In this paper, a remote control-based quantum computation tool is presented to ensure the trajectory tracking of a car-like mobile robot. In the proposed architecture, remote communication between the robot and the controller is achieved using quantum teleportation circuits. The controller is a classic PID controller, with its parameters optimized using a quantum-inspired particle swarm optimization (PSO) algorithm. The control scheme's performance is estimated using the root mean square error (RMSE), calculated from the tracking error, which is the difference between the reference position and the actual position of the robot. Simulation results show that the quantum-inspired PSO-based optimization of the PID controller yielded better performance in terms of prompt convergence and stability. Quantum teleportation also provided high accuracy when transferring control signals and measurement data. This work demonstrates that it is feasible to use quantum computing tools to enhance the real-time performance of long-distance, remotely controlled robotic systems, and that such telecontrol is inherently possible even at great distances or in hostile environments.
In this paper, we propose a novel algorithm based on Zidan’s quantum computing model for remotely controlling the direction of a quantum-controlled mobile robot equipped with n-movements. The proposed algorithm is based on the measurement of concurrence value for the different movements of the robot. Consider a faraway robot that moves in the deep space (e.g., moves toward a galaxy), and it is required to control the direction of this robot from a ground station by some person Alice. She sends an unknown qubit α |0⟩ + β |1⟩ via the teleportation protocol to the robot. Then, the proposed algorithm decodes the received unknown qubit into an angle θ, that determines the motion direction of the robot, based on the concurrence value. The proposed algorithm has been tested for four and eight movements. Two simulators have been tested; IBM Quantum composer and IBM’s system, The two simulators achieved the same result approximately. The motion of any part of the robot is considered, if it has a pre-existing sensor system and a locomotive system,. We can use this technique in many places like in space robots (16 directions). The results show that the proposed technique can be easily used for a huge number of movements. However, increasing the number of movements of the robot will increase the number of qubits.
We describe a quantum teleportation protocol for exchanging data between a mobile robot and its control station. Because of the high cost of quantum network systems, we use MATLAB software to simulate the teleportation of data. Our simulation models the dynamic motion of a car-like mobile robot (CLMR), considering its mass and inertia and the environmental viscosity. Our remote control method accurately reproduces a mathematical model of the CLMR’s real-world motion. The CLMR’s trajectory is represented by differential equations, with the velocity calculated using the Jacobian matrix. The velocity inputs are teleported from the control station to the CLMR, enabling it to move. Nevertheless, physical constraints cause the deviation of the robot’s trajectory from the predicted trajectory. To correct this deviation, the CLMR’s current position is teleported to the control station. Before implementing this protocol, we calculate the quantum teleportation circuit, and we use quantum gates in matrix form to simulate the data teleportation process. The protocol’s accuracy is assessed by comparing the original data and teleported data, and a good match is obtained. This study demonstrates the feasibility of quantum teleportation for remotely controlling real-time robotic systems over long distances and in environments that interfere with classical wireless communication.
This paper investigates the potential of quantum computing to revolutionize complex robotics, specifically focusing on optimization of robot control and movement. Traditional robotic control systems often struggle with complex environments and constraints, limiting the ability to achieve optimal performance. We propose a novel quantum algorithm designed to address these challenges by leveraging a dynamic, quantum-based simulation of the physical environment to generate constraints. This approach aims to enable robots to navigate and manipulate objects with unprecedented precision and adaptability. The core mechanism centers on utilizing a quantum solver to efficiently explore the search space of possible robot motions, guided by the simulation's feedback. This contrasts with traditional methods, which often struggle with the high dimensionality and complexity of robot dynamics. The research demonstrates the feasibility of this quantum-driven approach through simulations and preliminary experiments, showcasing potential improvements in robot control and movement.
The article considers a method for constructing a trajectory of a collaborative mobile robot using quantum computing in combination with classical optimization algorithms.The purpose of the study is to develop a mathematical model and numerical simulation of a quantum-oriented approach to constructing a trajectory of a collaborative robot, which allows minimizing energy costs in motion planning and ensuring obstacle avoidance in a dynamic environment.The scientific novelty of the work lies in the application of quantum optimization methods for multivariate planning, which allows avoiding local minima and guaranteeing the search for globally optimal solutions even in the case of complex configuration spaces.During the numerical simulation, it was demonstrated that the formed trajectories ensure successful obstacle avoidance and reaching the target point without deviations from the grid.Conclusions: analysis of the results showed stabilization of the energy function at the level of -350…-420, which confirms the effectiveness of optimization and convergence to the best solutions after 100-150 iterations.The constructed graphs confirmed that the robot's movement is consistent with the calculated quantum plans, and the deviation between the predicted and executed trajectories is minimized.The use of the energy efficiency criterion allowed us to evaluate different route construction scenarios, where the best plans stabilized with a margin of optimality relative to the worst options by 15-20%.Qualitative analysis of the constructed trajectories confirmed the consistency between the predicted and executed paths, and quantitative results proved a reduction in the number of steps when reaching the target point.The results obtained prove that the proposed method is promising for constructing reliable and energy-optimal trajectories in collaborative robotic systems Industry 5.0.
Localization is a critical aspect of mobile robotics, enabling robots to navigate their environment efficiently and avoid obstacles. Current probabilistic localization methods, such as the Adaptive-Monte Carlo localization (AMCL) algorithm, are computationally intensive and may struggle with large maps or high-resolution sensor data. This paper explores the application of quantum computing in robotics, focusing on the use of Grover's search algorithm to improve the efficiency of localization in mobile robots. We propose a novel approach to utilize Grover's algorithm in a 2D map, enabling faster and more efficient localization. Despite the limitations of current physical quantum computers, our experimental results demonstrate a significant speedup over classical methods, highlighting the potential of quantum computing to improve robotic localization. This work bridges the gap between quantum computing and robotics, providing a practical solution for robotic localization and paving the way for future research in quantum robotics.