arXiv subjects

Jinjie Li

Publications and source records attributed to Jinjie Li.

25 records · Page 2Linked to original sources

arXiv2024

Servo Integrated Nonlinear Model Predictive Control for Overactuated Tiltable-Quadrotors

Utilizing a servo to tilt each rotor transforms quadrotors from underactuated to overactuated systems, allowing for independent control of both attitude and position, which provides advantages for aerial manipulation. However, this enhancement also introduces model nonlinearity, sluggish servo response, and limited operational range into the system, posing challenges to dynamic control. In this study, we propose a control approach for tiltable-quadrotors based on nonlinear model predictive control (NMPC). Unlike conventional cascade methods, our approach preserves the full dynamics without simplification. It directly uses rotor thrust and servo angle as control inputs, where their limited working ranges are considered input constraints. Notably, we incorporate a first-order servo model within the NMPC framework. Simulation reveals that integrating the servo dynamics is not only an enhancement to control performance but also a critical factor for optimization convergence. To evaluate the effectiveness of our approach, we fabricate a tiltable-quadrotor and deploy the algorithm onboard at 100 Hz. Extensive real-world experiments demonstrate rapid, robust, and smooth pose-tracking performance.

cs.RO↗

arXiv2023

Fully Passive Measurement-Device-Independent Quantum Key Distribution

A recently proposed fully passive QKD removes all source modulator side channels. In this work, we combine the fully passive sources with MDI-QKD to remove simultaneously side channels from source modulators and detectors. We show a numerical simulation of the passive MDI-QKD, and we obtain an acceptable key rate while getting much better implementation security, as well as ease of implementation, compared with a recently proposed fully passive TF-QKD, paving the way towards more secure and practical QKD systems. We have proved that a fully passive protocol is compatible with MDI-QKD and we also proposed a novel idea that could potentially improve the sifting efficiency.

quant-ph↗

arXiv2023

Nonlinear MPC for Quadrotors in Close-Proximity Flight with Neural Network Downwash Prediction

Swarm aerial robots are required to maintain close proximity to successfully traverse narrow areas in cluttered environments. However, this movement is affected by the downwash effect generated from other quadrotors in the swarm. This aerodynamic effect is highly nonlinear and hard to describe through mathematical modeling. Additionally, the existence of the downwash disturbance can be predicted based on the states of neighboring quadrotors. If this prediction is considered, the control loop can proactively handle the disturbance, resulting in improved performance. To address these challenges, we propose an approach that integrates a Neural network Downwash Predictor with Nonlinear Model Predictive Control (NDP-NMPC). The neural network is trained with spectral normalization to ensure robustness and safety in uncollected cases. The predicted disturbances are then incorporated into the optimization scheme in NMPC, which enforces constraints to ensure that states and inputs remain within safe limits. We also design a quadrotor system, identify its parameters, and implement the proposed method on board. Finally, we conduct a prediction experiment to validate the safety and effectiveness of the network. In addition, a real-time trajectory tracking experiment is performed with the entire system, demonstrating a 75.37% reduction in tracking error in height under the downwash effect.

cs.RO↗

arXiv2023

Potato: A Data-Oriented Programming 3D Simulator for Large-Scale Heterogeneous Swarm Robotics

Large-scale simulation with realistic nonlinear dynamic models is crucial for algorithms development for swarm robotics. However, existing platforms are mainly developed based on Object-Oriented Programming (OOP) and either use simple kinematic models to pursue a large number of simulating nodes or implement realistic dynamic models with limited simulating nodes. In this paper, we develop a simulator based on Data-Oriented Programming (DOP) that utilizes GPU parallel computing to achieve large-scale swarm robotic simulations. Specifically, we use a multi-process approach to simulate heterogeneous agents and leverage PyTorch with GPU to simulate homogeneous agents with a large number. We test our approach using a nonlinear quadrotor model and demonstrate that this DOP approach can maintain almost the same computational speed when quadrotors are less than 5,000. We also provide two examples to present the functionality of the platform.

cs.RO↗

arXiv2023

Event-Triggered Optimal Formation Tracking Control Using Reinforcement Learning for Large-Scale UAV Systems

Large-scale UAV switching formation tracking control has been widely applied in many fields such as search and rescue, cooperative transportation, and UAV light shows. In order to optimize the control performance and reduce the computational burden of the system, this study proposes an event-triggered optimal formation tracking controller for discrete-time large-scale UAV systems (UASs). And an optimal decision - optimal control framework is completed by introducing the Hungarian algorithm and actor-critic neural networks (NNs) implementation. Finally, a large-scale mixed reality experimental platform is built to verify the effectiveness of the proposed algorithm, which includes large-scale virtual UAV nodes and limited physical UAV nodes. This compensates for the limitations of the experimental field and equipment in realworld scenario, ensures the experimental safety, significantly reduces the experimental cost, and is suitable for realizing largescale UAV formation light shows.

cs.MA↗

arXiv2022

Indoor Localization for Quadrotors using Invisible Projected Tags

Augmented reality (AR) technology has been introduced into the robotics field to narrow the visual gap between indoor and outdoor environments. However, without signals from satellite navigation systems, flight experiments in these indoor AR scenarios need other accurate localization approaches. This work proposes a real-time centimeter-level indoor localization method based on psycho-visually invisible projected tags (IPT), requiring a projector as the sender and quadrotors with high-speed cameras as the receiver. The method includes a modulation process for the sender, as well as demodulation and pose estimation steps for the receiver, where screen-camera communication technology is applied to hide fiducial tags using human vision property. Experiments have demonstrated that IPT can achieve accuracy within ten centimeters and a speed of about ten FPS. Compared with other localization methods for AR robotics platforms, IPT is affordable by using only a projector and high-speed cameras as hardware consumption and convenient by omitting a coordinate alignment step. To the authors' best knowledge, this is the first time screen-camera communication is utilized for AR robot localization.

cs.RO↗

arXiv2021

Butterfly Effect and Spatial Structure of Information Spreading in a Chaotic Cellular Automaton

Inspired by recent developments in the study of chaos in many-body systems, we construct a measure of local information spreading for a stochastic Cellular Automaton in the form of a spatiotemporally resolved Hamming distance. This decorrelator is a classical version of an Out-of-Time-Order Correlator studied in the context of quantum many-body systems. Focusing on the one-dimensional Kauffman Cellular Automaton, we extract the scaling form of our decorrelator with an associated butterfly velocity $v_b$ and a velocity-dependent Lyapunov exponent $λ(v)$. The existence of the latter is not a given in a discrete classical system. Second, we account for the behaviour of the decorrelator in a framework based solely on the boundary of the information spreading, including an effective boundary random walk model yielding the full functional form of the decorrelator. In particular, we obtain analytic results for $v_b$ and the exponent $β$ in the scaling ansatz $λ(v) \sim μ(v - v_b)^β$, which is usually only obtained numerically. Finally, a full scaling collapse establishes the decorrelator as a unifying diagnostic of information spreading.

cond-mat.stat-mech↗