arXiv subjects

Yanhui Zhang

Publications and source records attributed to Yanhui Zhang.

13 recordsLinked to original sources

arXiv2025

Bridging Probabilistic Inference and Behavior Trees: An Interactive Framework for Adaptive Multi-Robot Cooperation

This paper proposes an Interactive Inference Behavior Tree (IIBT) framework that integrates behavior trees (BTs) with active inference under the free energy principle for distributed multi-robot decision-making. The proposed IIBT node extends conventional BTs with probabilistic reasoning, enabling online joint planning and execution across multiple robots. It remains fully compatible with standard BT architectures, allowing seamless integration into existing multi-robot control systems. Within this framework, multi-robot cooperation is formulated as a free-energy minimization process, where each robot dynamically updates its preference matrix based on perceptual inputs and peer intentions, thereby achieving adaptive coordination in partially observable and dynamic environments. The proposed approach is validated through both simulation and real-world experiments, including a multi-robot maze navigation and a collaborative manipulation task, compared against traditional BTs(https://youtu.be/KX_oT3IDTf4). Experimental results demonstrate that the IIBT framework reduces BT node complexity by over 70%, while maintaining robust, interpretable, and adaptive cooperative behavior under environmental uncertainty.

cs.RO↗

arXiv2025

LLM-HBT: Dynamic Behavior Tree Construction for Adaptive Coordination in Heterogeneous Robots

We introduce a novel framework for automatic behavior tree (BT) construction in heterogeneous multi-robot systems, designed to address the challenges of adaptability and robustness in dynamic environments. Traditional robots are limited by fixed functional attributes and cannot efficiently reconfigure their strategies in response to task failures or environmental changes. To overcome this limitation, we leverage large language models (LLMs) to generate and extend BTs dynamically, combining the reasoning and generalization power of LLMs with the modularity and recovery capability of BTs. The proposed framework consists of four interconnected modules task initialization, task assignment, BT update, and failure node detection which operate in a closed loop. Robots tick their BTs during execution, and upon encountering a failure node, they can either extend the tree locally or invoke a centralized virtual coordinator (Alex) to reassign subtasks and synchronize BTs across peers. This design enables long-term cooperative execution in heterogeneous teams. We validate the framework on 60 tasks across three simulated scenarios and in a real-world cafe environment with a robotic arm and a wheeled-legged robot. Results show that our method consistently outperforms baseline approaches in task success rate, robustness, and scalability, demonstrating its effectiveness for multi-robot collaboration in complex scenarios.

cs.RO↗

arXiv2024

BMO on Weighted Bergman Spaces over Tubular Domains

In this paper, we characterize Bounded Mean Oscillation (BMO) and establish their connection with Hankel operators on weighted Bergman spaces over tubular domains. By utilizing the space BMO, we provide a new characterization of Bloch spaces on tubular domains. Next, we define a modified projection operator and prove its boundedness. Furthermore, we introduce differential operators and demonstrate that these operators belong to Lebesgue spaces on tubular domains. Finally, we establish an integral representation for Bergman functions using these differential operators.

math.CV↗

arXiv2024

USLC: Universal Self-Learning Control via Physical Performance Policy-Optimization Neural Network

This study addresses the challenge of achieving real-time Universal Self-Learning Control (USLC) in nonlinear dynamic systems with uncertain models. The proposed control method incorporates a Universal Self-Learning module, which introduces a model-free online executor-evaluator framework to enable controller adaptation in the presence of unknown disturbances. By leveraging a neural network model trained on historical system performance data, the controller can autonomously learn to approximate optimal performance during each learning cycle. Consequently, the controller's structural parameters are incrementally adjusted to achieve a performance threshold comparable to human-level performance. Utilizing nonlinear system stability theory, specifically in the context of three-dimensional manifold space, we demonstrate the stability of USLC in Lipschitz continuous systems. We illustrate the USLC framework numerically with two case studies: a low-order circuit system and a high-order morphing fixed-wing attitude control system. The simulation results verify the effectiveness and universality of the proposed method.

eess.SY↗

arXiv2024

Low-cost adaptive obstacle avoidance trajectory control for express delivery drone

This paper studies quadcopters obstacle avoidance trajectory control (OATC) problem for express delivery. A new nonlinear adaptive learning controller that is low-cost and portable to different wheelbase sizes is proposed to adapt to large-angle maneuvers and load changes in UAV delivery missions. The controller consists of a nonlinear variable gain (NLVG) function and an extreme value search (ES) algorithm to reduce overshoot and settling time. Finally, simulations were conducted on a quadcopter to verify the effectiveness of the proposed control scheme under two typical collision-free trajectories.

eess.SY↗

arXiv2023

Two types of narrow-sense negacyclic BCH codes

Negacyclic BCH codes are an important subclass of negacyclic codes and are the best linear codes in most cases, but their parameters are hard to determine. In this paper, we mainly study two types of negacyclic BCH codes of length $n=\frac{q^{m}-1}{4},\frac{q^{m}+1}{4}$, and give their dimensions and the lower bound on their minimum distance. Furthermore, we provide the weight distribution of narrow-sense neagcyclic BCH codes of length $n=\frac{q^m-1}{4}$ for some special designed distances.

cs.IT↗

arXiv2023

A class of LCD BCH codes of length $n=\frac{q^{m}+1}λ$

LCD BCH codes are an important class of cyclic codes which have efficient encoding and decoding algorithms, but their parameters are difficult to determine. The objective of this paper is to study the LCD BCH codes of length $n=\frac{q^{m}+1}λ$, where $λ\mid (q+1)$ is an integer. Several types of LCD BCH codes with good parameters are presented, and many optimal linear codes are settled. Moreover, we present the first few largest coset leaders modulo $n=q^{m}+1, \frac{q^{m}+1}{2},\frac{3^{m}+1}{4}$, and partially solve two conjectures about BCH codes.

cs.IT↗

arXiv2022

Three classes of BCH codes and their duals

BCH codes are an important class of cyclic codes, and have wide applicantions in communication and storage systems. However, it is difficult to determine the parameters of BCH codes and only a few cases are known. In this paper, we mainly study three classes of BCH codes with $n=q^{m}-1,\frac{q^{2s}-1}{q+1},\frac{q^{m}-1}{q-1}$. On one hand, we accurately give the parameters of $\mathcal C_{(q,n,δ,1)}$ and its dual codes. On the other hand, we give the sufficient and necessary conditions for $\mathcal C_{(q,n,δ,2)}$ being dually-BCH codes.

cs.IT↗

arXiv2021

Atomistic simulations of surface reactions in ultra-high-temperature ceramics: O2, H2O and CO adsorption and dissociation on ZrB2 (0001) surfaces

Understanding surface reactivity is crucial in many fields, going from heterogeneous catalysis to materials oxidation and corrosion. In order to decipher the surface reactions of ZrB2 exposed to the harsh environment of aerospace components, the chemical activity of both Zr- and B-surfaces is predicted and compared by using density functional theory and nudged elastic band methods. In particular the adsorption, dissociation and diffusion of O2, CO and H2O are extensively examined through the calculation of surface adsorption energies and reaction pathways. We find the dissociative adsorption of O2 dominating the reactivity of ZrB2 surfaces, while the dissociation of H2O and CO is weakly active on Zr-surfaces, and even less activated on B-terminated ones. Importantly, we discover that the reaction of O2 and H2O can trigger strong surface reconstruction at B-surfaces. Our work thus provides significant insights into the diverse adsorption and reaction mechanisms of ZrB2 surfaces.

cond-mat.mtrl-sci↗

arXiv2019

Pushing the limits of atomistic simulations towards ultra-high temperature: a machine-learning force field for ZrB2

Determining thermal and physical quantities across a broad temperature domain, especially up to the ultra-high temperature region, is a formidable theoretical and experimental challenge. At the same time it is essential for understanding the performance of ultra-high temperature ceramic (UHTC) materials. Here we present the development of a machine-learning force field for ZrB2, one of the primary members of the UHTC family with a complex bonding structure. The force field exhibits chemistry accuracy for both energies and forces and can reproduce structural, elastic and phonon properties, including thermal expansion and thermal transport. A thorough comparison with available empirical potentials shows that our force field outperforms the competitors. Most importantly, its effectiveness is extended from room temperature to the ultra-high temperature region (up to ~ 2,500 K), where measurements are very difficult, costly and some time impossible. Our work demonstrates that machine-learning force fields can be used for simulations of materials in a harsh environment, where no experimental tools are available, but crucial for a number of engineering applications, such as in aerospace, aviation and nuclear.

cond-mat.mtrl-sci↗

arXiv2019

Interface engineering of graphene nanosheet reinforced ZrB$_2$ composites by tuning surface contacts

The mechanical properties of heterophase interfaces are critically important for the behaviour of graphene-reinforced composites. In this work, the structure, adhesion, cleavage and sliding of heterophase interfaces, formed between a ZrB$_2$ matrix and graphene nanosheets, are systematically investigated by density functional theory, and compared to available experimental data. We demonstrate that the surface chemistry of the ZrB$_2$ matrix material largely shapes the interface structures (of either Zr-C-Zr or B-C-B type) and the nature of the interfacial interaction. The Zr-C-Zr interfaces present strong chemical bonding and their response to mechanical stress is significantly influenced by graphene corrugation. In contrast B-C-B interfaces, interacting through the relatively weak $π$-$π$ stacking, show attributes similar to 2D materials heterostructures. Our theoretical results provide insights into the interface bonding mechanisms in graphene/ceramic composites, and emphasize the prospect for their design via interface engineering enabled by surface contacts.

cond-mat.mtrl-sci↗

arXiv2019

Geometry of quantum evolution in a nonequilibrium environment

We theoretically study the geometric effect of quantum dynamical evolution in the presence of a nonequilibrium noisy environment. We derive the expression of the time dependent geometric phase in terms of the dynamical evolution and the overlap between the time evolved state and initial state. It is shown that the frequency shift induced by the environmental nonequilibrium feature plays a crucial role in the geometric phase and evolution path of the quantum dynamics. The nonequilibrium feature of the environment makes the length of evolution path becomes longer and reduces the dynamical decoherence and non-Markovian behavior in the quantum dynamics.

quant-ph↗

arXiv2010

Weak field magnetoresistance of narrow-gap semiconductors InSb

The magnetoresistance of InSb has been intensively investigated. The experiments we perform here focus on weak field magnetoresistance of InSb thin film. We investigate the magnetoresistance of InSb films in perpendicular, tilted as well as parallel magnetic field. Our results verify the previous observations concerning weak localization effect in InSb thin film. Moreover, we systematically study the anisotropy of magnetoresistance of InSb. We find that the existence of in-plane field can effectively suppress the weak localization effect of InSb film. We fit the experimental data with two types of models, the match between data and model is excellent. From the fitting procedure, we get information about phase coherence time, spin-orbit scattering time. The information about Zeeman effect and sample roughness are also extracted from the fitting procedure.

cond-mat.mtrl-sci↗