Xingkai Yu | Mobile Robotics Systems | Innovative Research Award

Published on by Robotics and Automation

Innovative Research Award

Xingkai Yu — North China Electric Power University, China

Researcher Information
Affiliation North China Electric Power University
Country China
Scopus ID 57201419537
Documents 34
Citations 403
h-index 11
Subject Area Mobile Robotics Systems
Event International Robotics and Automation Awards
ORCID 0000-0002-7422-7406

Xingkai Yu is a researcher affiliated with North China Electric Power University whose documented research includes robotic swarm coordination, battery state-of-charge estimation, control systems, and intelligent electrical-system analysis. His publication record includes work addressing distributed robotic coverage and advanced estimation methods for lithium batteries. [1]

Abstract

The Innovative Research Award recognizes research activity demonstrating methodological development, interdisciplinary relevance, and potential practical value. Xingkai Yu’s documented work spans mobile robotic swarm coordination, battery state estimation, control, and intelligent electrical-system analysis, providing evidence of research engagement across robotics and automation-related engineering domains. [1] [2]

Keywords

Keywords: Mobile Robotics Systems; Robotic Swarms; Anti-Flocking; Dynamic Coverage; Battery State Estimation; Kalman Filtering; Intelligent Control; Automation; Fault Detection.

Introduction

Xingkai Yu’s research profile reflects interdisciplinary work connecting robotics, automation, control, and intelligent energy systems. His research includes distributed robotic-swarm coordination for dynamic coverage and algorithmic approaches to lithium-battery state estimation. These studies address autonomous decision-making, estimation, and control problems relevant to modern cyber-physical engineering systems. [2]

Research Profile

The available publication evidence indicates a research profile centered on intelligent systems and engineering automation. Relevant areas include mobile robotic swarms, distributed coordination, nonlinear estimation, battery-management algorithms, and electrical fault analysis. This combination demonstrates an applied research orientation involving sensing, computation, control, and autonomous system decision processes. [3]

Research Contributions

A principal contribution is research on dynamic coverage using self-organized robotic swarms and an anti-flocking mechanism, addressing distributed coordination in mobile robots. Another contribution concerns lithium-battery state-of-charge estimation through an improved firefly-algorithm-optimized dual extended Kalman filter. Together, these studies demonstrate algorithmic work in autonomous coordination and intelligent estimation. [1]

Publications

The selected publications illustrate the breadth of the research record. The robotic-swarm study develops anti-flocking models for dynamic coverage, while the battery study addresses state-of-charge estimation using an optimized dual extended Kalman filtering framework. A related series AC arc-fault study using singular-spectrum statistical features further demonstrates the wider application of signal-processing and intelligent-analysis methods.

  • Sun, X., Duan, X., Dai, J., Qu, Z., Yu, X., & Jin, G. (2026). Dynamic coverage of self-organized robotic swarm via anti-flocking mechanism. Aerospace Science and Technology. https://doi.org/10.1016/j.ast.2026.113061 [1]
  • Du, Y., Yu, X., Jin, G., & Li, J. (2026). Lithium battery state of charge estimation based on improved firefly algorithm optimized dual extended Kalman filter. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/TIE.2026.3675113 [2]
  • Xiong, D., Yang, S., Xue, Y., Zhang, P., Song, R., & Song, J. (2025). Fast identification of series arc faults based on singular spectrum statistical features. Electronics, 14(16), 3337. https://doi.org/10.3390/electronics14163337 [3]

Research Impact

The research has potential relevance to autonomous robotics, intelligent transportation and energy-management technologies. Distributed swarm coverage addresses coordination in multi-robot environments, while battery state estimation supports reliable monitoring within battery-management systems. Signal-analysis research on arc faults illustrates the broader applicability of computational methods to intelligent electrical safety and monitoring. [2] [3]

Award Suitability

The documented research provides a reasonable basis for consideration for an Innovative Research Award because it includes peer-reviewed work addressing algorithmic innovation in robotic coordination and intelligent estimation. The combination of mobile robotics, autonomous swarm behavior, control, and computational signal processing aligns with research themes commonly associated with robotics and automation. [3]

Conclusion

Xingkai Yu’s documented research combines robotic swarm coordination, intelligent estimation, and engineering-oriented computational methods. The selected publications demonstrate relevance to autonomous systems and automation through distributed coverage, optimized battery estimation, and signal-based fault analysis. On this evidence, the research profile presents a substantive basis for consideration under an innovation-focused robotics award. [1] [2] [3]

References

  1. Dynamic Coverage of Self-organized Robotic Swarm Via Anti-flocking Mechanism.
    https://www.researchgate.net/publication/408338309_Dynamic_Coverage_of_Self-organized_Robotic_Swarm_Via_Anti-flocking_Mechanism
  2. Lithium Battery State of Charge Estimation Based on Improved Firefly Algorithm Optimized Dual Extended Kalman Filter.
    https://www.researchgate.net/publication/403377066_Lithium_Battery_State_of_Charge_Estimation_Based_on_Improved_Firefly_Algorithm_Optimized_Dual_Extended_Kalman_Filter
  3. A Series AC Arc Fault Detection Method Based on Singular Spectrum Analysis
    /i>(16), 3337.
    https://www.mdpi.com/2079-9292/9/9/1367
  4. Elsevier. (n.d.). Scopus author details: Xingkai Yu, Author ID 57201419537. Scopus.
    https://www.scopus.com/pages/authors/57201419537

Dr. Maria Muzamil Memon | Robotics | Research Excellence Award

Published on by Robotics and Automation

Dr. Maria Muzamil Memon | Robotics | Research Excellence Award

Harbin Institute of Technology | China

Dr. Maria Muzamil Memon is a dedicated researcher and postdoctoral fellow at the Harbin Institute of Technology, China, specializing in micro-electro-mechanical systems , microfluidics, and flexible sensor technologies. she earned her Phd in electronic engineering from the university of electronic science and technology of China, where she focused on aln-based surface acoustic wave sensors and significantly improved pressure sensitivity through innovative structural design, validated via comsol-based finite element analysis. Her academic journey includes a master’s degree in mechanical engineering from Harbin institute of technology and a bachelor’s degree in electronics engineering from Mehran University of engineering and technology. Throughout her career, she has worked extensively on microfluidic chip fabrication, biomedical device development, and multiphysics simulations, Robotics while also supervising undergraduate and postgraduate students. Dr. Memon has received multiple prestigious awards, including several academic achievement and excellent performance awards from UESTC, and she is a two-time recipient of the Chinese government scholarship. her research impact is reflected in 141 citations, an h-index of 7, and 6 documented publications, i10-index, demonstrating her growing influence in the fields of mems sensors, sensing materials, and microfluidic systems.

Profile: Google Scholar

Featured Publications

Memon, M. M., Liu, Q., Manthar, A., Wang, T., & Zhang, W. (2023). Surface acoustic wave humidity sensor. Micromachines, 14(5), 945.

Memon, M. M., Hongyuan, Y., Pan, S., Wang, T., & Zhang, W. (2022). Surface acoustic wave humidity sensor based on hydrophobic polymer film. Journal of Electronic Materials, 51(10), 5627–5634.

Memon, M. M., Pan, S., Wan, J., Wang, T., & Zhang, W. (2021). Highly sensitive thick diaphragm-based surface acoustic wave pressure sensor. Sensors and Actuators A: Physical, 331, 112935.

Memon, M. M., Pan, S., Wan, J., Wang, T., Peng, B., & Zhang, W. (2022). Sensitivity enhancement of SAW pressure sensor based on the crystalline direction. IEEE Sensors Journal, 22(10), 9329–9335.

Memon, M. M., Pan, S., Wan, J., Wang, T., Peng, B., & Zhang, W. (2022). Sensitivity enhancement of SAW pressure sensor based on the crystalline direction. IEEE Sensors Journal, 22(10), 9329–9335.

Dr. Lanxiang Zheng – Mobile Robotics Systems – Best Researcher Award

Published on by Robotics and Automation

Dr. Lanxiang Zheng - Mobile Robotics Systems - Best Researcher Award

China United Network Communications Co., Ltd. Guangdong Branch - China

Author Profile

ORCID

Summary

Lanxiang Zheng is an accomplished ai technology director with a strong academic foundation rooted in computer science and robotics. after earning his ph.d. from sun yat-sen university, he dedicated his career to advancing research in distributed control, uav swarm planning, and multi-robot exploration. professionally, he leads innovations at china united network communications co., ltd. guangdong branch, applying theoretical research to real-world ai systems. his work uniquely combines intelligent robotics with power electronics, enhancing system efficiency and control. he is a recognized reviewer for major robotics journals and conferences, contributing significantly to the academic community.

Early academic pursuits

Lanxiang Zheng began his academic journey with a strong focus on computer science, eventually earning a ph.d. from sun yat-sen university. during his formative years, he developed deep expertise in distributed systems and intelligent control algorithms. his academic foundation laid the groundwork for his later contributions in the fields of multi-robot exploration and Mobile Robotics Systems uav swarm planning. even during this phase, he explored the interplay between artificial intelligence and power electronics, particularly in intelligent embedded systems for robotics.

Professional endeavors

After completing his doctorate, zheng took on the role of ai technology director at china united network communications co., ltd., guangdong branch. in this capacity, he leads several r&d initiatives focusing on real-time applications of ai in industrial and telecommunications settings. his work bridges theory and practice, bringing cutting-edge robotics research into Mobile Robotics Systems practical implementations. one of his key areas involves integrating power electronics with swarm robotics to enhance energy efficiency and operational control in field-deployed systems.

Contributions and research focus

Lanxiang Zheng’s primary research areas include distributed control, uav swarm planning, and embodied intelligence. his work in multi-robot exploration has advanced the autonomous capabilities of mobile robots in complex environments. he is particularly known for pioneering adaptive swarm algorithms that incorporate distributed intelligence, which are instrumental in Mobile Robotics Systems scalable robotic deployments. his research also investigates the convergence of intelligent control strategies with power electronics, enhancing the synergy between hardware control and machine learning models.

Impact and influence

As a recognized reviewer for prestigious journals and conferences such as ra-l, icar, and iros, zheng has played an important role in maintaining the quality and innovation within the ai and robotics research community. his evaluation work supports groundbreaking studies and Mobile Robotics Systems reinforces academic standards globally. he is frequently consulted on topics related to ai integration in industrial robotics and autonomous systems, often emphasizing the importance of efficient power electronics in ensuring real-world scalability.

Academic cites

Lanxiang Zheng’s scholarly work has been widely cited across robotics and ai research. his publications contribute to foundational knowledge in uav autonomy, swarm coordination, and intelligent control systems. his citations reflect the academic community’s recognition of his theoretical advancements and practical methodologies. his research articles are frequently referenced in Mobile Robotics Systems studies exploring the control mechanics of collaborative robotics and the embedded system design for energy-efficient robotics.

Legacy and future contributions

Zheng’s interdisciplinary approach and visionary leadership have made a lasting mark in the robotics sector. he aims to continue driving innovation at the intersection of artificial intelligence, robotics, and Mobile Robotics Systems communications infrastructure. his future projects focus on large-scale deployment of intelligent agents, supported by advanced power electronics, to tackle real-world challenges such as disaster response, environmental monitoring, and smart city automation. his legacy lies in building intelligent, collaborative systems that push the boundaries of what robots can achieve autonomously.

Notable Publications

  1. Title: AAGE: Air-Assisted Ground Robotic Autonomous Exploration in Large-Scale Unknown Environments
    Authors: Lanxiang Zheng, Mingxin Wei, Ruidong Mei, Kai Xu, Junlong Huang, Hui Cheng
    Journal: IEEE Transactions on Robotics
    Year: 2025
  2. Title: Meta-Learning Enhanced Model Predictive Contouring Control for Agile and Precise Quadrotor Flight
    Authors: Mingxin Wei, Lanxiang Zheng, Ying Wu, Ruidong Mei, Hui Cheng
    Journal: IEEE Transactions on Robotics
    Year: 2025
  3. Title: Bio-Inspired Decentralized Model Predictive Flocking Control for UAV Swarm Trajectory Tracking
    Authors: Lanxiang Zheng, Ruidong Mei, Mingxin Wei, Zhijun Zhao, Bingzhi Zou
    Journal: Journal of Bionic Engineering
    Date: 2025-06-23
  4. Title: Real-Time Efficient Environment Compression and Sharing for Multi-Robot Cooperative Systems
    Authors: Lanxiang Zheng, Kai Xu, Jinqi Jiang, Mingxin Wei, Boyu Zhou, Hui Cheng
    Journal: IEEE Transactions on Intelligent Vehicles
    Year: 2024
  5. Title: Safe Learning-Based Control for Multiple UAVs Under Uncertain Disturbances
    Authors: Mingxin Wei, Lanxiang Zheng, Ying Wu, Han Liu, Hui Cheng
    Journal: IEEE Transactions on Automation Science and Engineering
    Year: 2024

Conclusion

Through a blend of academic rigor and professional application, Lanxiang Zheng has become a key figure in ai-driven robotics. his research not only deepens understanding of swarm intelligence and autonomous systems but also paves the way for practical deployment powered by advanced power electronics. his continued efforts promise to influence the future of intelligent machines, making them more efficient, scalable, and impactful across industries.