Магид Евгений Аркадьевич

Московский институт электроники и математики им. А.Н. Тихонова

Профиль на hse.ru ↗ тел.: +7 (495) 772-95-90 | 15198

Публикаций

114

Языков

Наград

Конференций

Профиль Публикации (114) Курсы (2)

Профессиональные интересы

робототехникамобильные роботывзаимодействие человека и робота

Должности

Профессор — Московский институт электроники и математики им. А.Н. Тихонова, Департамент электронной инженерии

Био

· Начал работать в НИУ ВШЭ в 2021 году.

Образование

2011 · PhD: Университет Цукубы
2006 · Магистратура: Израильский технологический институт Технион, специальность «Прикладная математика», квалификация «Магистр»

Опыт работы

· 2016: С по н.в.: Профессор, заведующий кафедрой интеллектуальной робототехники, основатель и руководитель «Лаборатории Интеллектуальных Робототехнических Систем», руководитель проекта «Робототехническое Инженерное Образование» (РобИО), Институт информационных технологий и интеллектуальных систем (ИТИС), Казанский (Приволжский) Федеральный Университет, г. Казань, Республика Татарстан, Россия. С
· 2017: по н.в.: Директор магистерской программы «Интеллектуальная робототехника», Институт информационных технологий и интеллектуальных систем (ИТИС), Казанский (Приволжский) Федеральный Университет, г. Казань, Республика Татарстан, Россия
· 2020: : Приглашенный лектор, Национальный университет науки и технологий Юньлиня, г. Доулю, Юньлинь, Тайвань
· 2014-2016: : Профессор, основатель и руководитель «Лаборатории Интеллектуальных Робототехнических Систем», Университет Иннополис, г. Иннополис, Республика Татарстан, Россия
· 2014: : Научный консультант по робототехнике, Нижегородский государственный университет им. Н.И. Лобачевского
· 2013-2014: : Старший научный сотрудник с докторской ученой степенью, Бристольская робототехническая лаборатория и Бристольский университет (The Bristol Robotics Laboratory and The University of Bristol), г. Бристоль, Великобритания
· 2012-2013: : Научный сотрудник с докторской ученой степенью, Институт робототехники, Университет Карнеги Меллон (The Robotics Institute, Carnegie Mellon University), г. Питтсбург, Пенсильвания, США
· 2011-2012: : Научный сотрудник с докторской ученой степенью, Цукубский Университет (University of Tsukuba), г. Цукуба, Япония
· 2011: : Младший научный сотрудник, АИСТ-Национальный институт передовых технических наук и технологий (AIST - National Institute of Advanced Industrial Science and Technology), г. Цукуба, Япония
· 2006-2007: : Независимый исследователь, Цукубский Университет (University of Tsukuba), г. Цукуба, Япония
· 2002-2006: : Старший преподаватель, Технион - Израильский технологический институт (Technion - Israel Institute of Technology), Хайфа, Израиль
· 2004-2005: : Дизайнер курса и лектор, Инженерный колледж Орт Хермелин (ORT Hermelin College of Engineering), Нетания, Израиль
· 2001-2003: : Преподаватель, Технион - Израильский технологический институт (Technion - Israel Institute of Technology), Хайфа, Израиль
· 2003-2004: : Студент по обмену (Магистратура, Израиль-Япония), Цукубский Университет (University of Tsukuba), г. Цукуба, Япония
· 2002: : Технический ассистент, Технион - Израильский технологический институт (Technion - Israel Institute of Technology), Хайфа, Израиль

Награды и поощрения

· Надбавка за публикацию в журнале из Списка А (и приравненном к нему научном издании) (2025–2026, 2024–2025, 2023–2024)
· Надбавка за публикацию в международном рецензируемом научном издании (2022–2023)

Гранты и проекты

— · Название проекта: «Разработка и исследование комплекса программных решений создания энергоэкономичных систем управления механикой движения антропоморфных робототехнических комплексов на основе контроля статического и динамического равновесия».
— · Название проекта: Локализация, картографирование и поиск пути для беспилотного наземного робота (БНР) при помощи группы беспилотных летательных аппаратов (БПЛА) с использованием активного коллективного технического зрения и планированием в общем доверительном пространстве группы роботов.
— · Название проекта: Робототехническое инженерное образование
— · Название проекта: Проект организации IV Всероссийского научно-практического семинара «Беспилотные транспортные средства с элементами искусственного интеллекта» (БТС-ИИ-2017).
— · Название проекта: Исследование и разработка методов автономной калибровки и анализа положения конечностей антропоморфного робота на основе изображения, полученного с одной камеры.
— · Название проекта: Разработка системы управления роботизированным лапароскопическим инструментом для автономного сшивания тканей.
— · Название проекта: Автономная калибровка бортовых камер робототехнической системы с использованием координатных меток, нанесенных на поверхность робота.
— · Название проекта: РобИО-Маг - Робототехническое Инженерное Образование: создание первой российской Магистерской программы по робототехнике на основе опыта ведущих зарубежных вузов.
— · Название проекта: Разработка программного комплекса системы управления с функцией автономного возврата и графическим интерфейсом для гусеничного мобильного робототехнического комплекса (РТК).
— · Название проекта: Информационная система управления чрезвычайными ситуациями в зонах наводнений и оползней при помощи распределенной гетерогенной группы роботов.
— · Название проекта: Разработка нового калибровочного шаблона и алгоритма калибровки для бортовых камер мобильного робота.
— · Название проекта: создание нового учебного курса «Навигация мобильных робототехнических систем (НАРС)».
— · Название проекта: Разработка и исследование цифровых объектов робототехнических симуляторов, включая динамические модели человека.
— · Название проекта: Разработка, программная реализация и экспериментальная валидация протокола прикладного уровня для обмена данными между мобильными роботами в условиях проведения поисково-спасательных работ.
— · Название проекта: «НИЛ МедРо – Медицинская робототехника».
— · Название проекта: участие в международной конференции.
— · Название проекта: Навигация для спасательного робота.
— · Название проекта: Навигация для спасательного робота.
— · Название проекта: Спасательная робототехника.
— · Название проекта: Планирование пути для мобильного робота.

Конференции (22)

Показать все

· 2021: IEEE Conference on Industrial Electronics and Applications (Chengdu). Доклад: Kiryanov D., Lavrenov R., Safin R., Svinin M., Magid E. Mobile application for controlling multiple robots // Proceedings of the IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) (Chengdu, China; 01-02 August 2021) - p. 1913-1917
· 2021: International Conference on Artificial Life and Robotics, ICAROB 2021 (Беппу). Доклад: Bulatov, S., Kharisova, E., Dudin, V., Khazetdinov, A., Lavrenov, R., Magid, E. (2021). Architecture of a student training computer program for preparing professional outpatient consulting skills within an electronic medical records system during COVID-19 alertness situation. International Conference on Artificial Life and Robotics (ICAROB 2021), p. 36-39.
· 2021: IEEE International Conference on Intelligent Robots and Systems (IROS 2021) (Прага). Доклад: Talanov, M., Suleimanova, A., Leukhin, A., Mikhailova, Y., Toschev, A., Militskova, A., Lavrov, I., Magid, E. (2021). Neurointerface implemented with Oscillator Motifs. Proceedings of IEEE International Conference on Intelligent Robots and Systems (IROS 2021)
· 2021: The 18th International Conference on Ubiquitous Robots (2021) (Gangneung-si, Gangwon-do). Доклад: Ma, J., Guo, D., Bai, Y., Svinin, M., Magid, E. (2021). A Vision-Based Robust Adaptive Control for Caging a Flood Area Via Multiple UAVs. The 18th International Conference on Ubiquitous Robots (UR 2021), p. 386-391.
· 2021: XV International Siberian Conference on Control and Communications (SIBCON-2021) (Казань). Доклад: Abbyasov, B., Dobrokvashina, A., Lavrenov, R., Kharisova, E., Tsoy, T., Gavrilova, L., Bulatov, S., Maslak, E., Schiefermeier-Mach, N., Magid, E. (2021). Ultrasound sensor modeling in Gazebo simulator for diagnostics of abdomen pathologies. The 15th Siberian Conference on Control and Communications (SIBCON 2021), № 9438910.
· 2021: XV International Siberian Conference on Control and Communications (SIBCON-2021) (Казань). Доклад: Guo, D., Bai, Y., Svinin, M., Magid, E. (2021). Robust Adaptive Multi-Agent Coverage Control for Flood Monitoring. The 15th Siberian Conference on Control and Communications (SIBCON 2021), № 9438872.
· 2021: XV International Siberian Conference on Control and Communications (SIBCON-2021) (Казань). Доклад: Tsoy, T., Safin, R., Magid, E., Saha, S. K. (2021). Estimation of 4-DoF manipulator optimal configuration for autonomous camera calibration of a mobile robot using on-board templates. The 15th Siberian Conference on Control and Communications (SIBCON 2021), № 9438925.
· 2021: XV International Siberian Conference on Control and Communications (SIBCON-2021) (Казань). Доклад: Khazetdinov, A., Zakiev, A., Tsoy, T., Svinin, M., Magid, E. (2021). Embedded ArUco: a novel approach for high precision UAV landing. The 15th Siberian Conference on Control and Communications (SIBCON 2021), № 9438855.
· 2021: XV International Siberian Conference on Control and Communications (SIBCON-2021) (Казань). Доклад: Carvajal, I., Martinez-Garcia, E.A., Lavrenov, R., Magid, E. (2021). Robot arm planning and control by τau-Jerk theory and a vision-based recurrent ANN observer. The 15th Siberian Conference on Control and Communications (SIBCON 2021), № 9438857.
· 2021: XV International Siberian Conference on Control and Communications (SIBCON-2021) (Казань). Доклад: Safin, R., Lavrenov, R., Hsia, K.-H., Maslak, E., Schiefermeier-Mach, N., Magid, E. (2021). Modelling a TurtleBot3 Based Delivery System for a Smart Hospital in Gazebo. The 15th Siberian Conference on Control and Communications (SIBCON 2021), № 9438875.
· 2020: International Conference on Machine Vision 2020 (Рим). Доклад: Imameev D., Zakiev A., Tsoy T., Bai Y., Svinin M., Magid E. LIDAR-based Parking Spot Search Algorithm // The 13th International Conference on Machine Vision (ICMV), 1160502
· 2020: 13th International Conference on Developments in eSystems Engineering (DeSE 2020) (virtual). Доклад: Chebotareva, E., Magid, E., Carballo, A., Hsia, K.-H. (2020). Basic User Interaction Features for Human-Following Cargo Robot TIAGo Base. Proceedings of 13th International Conference on Developments in eSystems Engineering (DeSE), p. 206-211.
· 2020: 13th International Conference on Developments in eSystems Engineering (DeSE 2020) (virtual). Доклад: Gavrilova, L., Kotik, A., Tsoy, T., Martinez-Garcia, E.A., Svinin, M., Magid, E. (2020). Facilitating a preparatory stage of real-world experiments in a humanoid robot assisted English language teaching using Gazebo simulator. Proceedings of 13th International Conference on Developments in eSystems Engineering (DeSE), p. 222-227.
· 2020: 13th International Conference on Developments in eSystems Engineering (DeSE 2020) (virtual). Доклад: Shafikov, A., Tsoy, T., Lavrenov, R., Magid, E., Li, H., Maslak, E., Schiefermeier-Mach, N. (2020). Medical palpation autonomous robotic system modeling and simulation in ROS/Gazebo. Proceedings of 13th International Conference on Developments in eSystems Engineering (DeSE), p. 200-205.
· 2020: 17th International conference on ubiquitous robots (Киото). Доклад: Bai, Y., Asami, K., Svinin, M., Magid, E. (2020). Cooperative Multi-Robot Control for Monitoring an Expanding Flood Area. Proceedings of the 17th International conference on ubiquitous robots, p. 500-505.
· 2020: 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE 2020) (Chiang Mai). Доклад: Bai, Y., Svinin, M., Magid, E. (2020). Multi-Robot Control for Adaptive Caging and Tracking of a Flood Area. 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), p. 1452-1457.
· 2020: 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE 2020) (Chiang Mai). Доклад: Safin, R., Garipova, E., Lavrenov, R., Li, H., Svinin, M., Magid, E. (2020). Hardware and Software Video Encoding Comparison. Proceedings of 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), p. 924-929.
· 2020: International Joint Conference on Neural Networks (IJCNN 2020) (Глазго). Доклад: Zakiev, A., Tsoy T., Shabalina, K., Magid, E., Saha, S.K. (2020). Virtual Experiments on ArUco and AprilTag Systems Comparison for Fiducial Marker Rotation Resistance under Noisy Sensory Data. Proceedings of the International Joint Conference on Neural Networks (IJCNN), p. 1-6, doi: 10.1109/IJCNN48605.2020.9207701.
· 2020: International Conference on Robotics and Automation (ICRA 2020) (Париж). Доклад: Abbyasov, B., Lavrenov, R., Zakiev, A., Yakovlev, K., Svinin, M., Magid, E. (2020). Automatic Tool for Gazebo World Construction: From a Grayscale Image to a 3D Solid Model. International Conference on Robotics and Automation (ICRA), 2020, p. 7226-7232.
· 2020: 23rd International Conference on Climbing and Walking Robots and Support Technologies for Mobile Machines (CLAWAR 2020) (Москва). Доклад: Abbyasov, B., Lavrenov, R., Zakiev, A., Tsoy, T., Magid, E., Svinin, M., Martinez-Garcia, E.A. (2020). Comparative analysis of ROS-based centralized methods for conducting collaborative monocular visual SLAM using a pair of UAVs. Proceedings of the 23rd International Conference on Climbing and Walking Robots and Support Technologies for Mobile Machines (CLAWAR 2020), p. 113-120.
· 2020: 23rd International Conference on Climbing and Walking Robots and Support Technologies for Mobile Machines (CLAWAR 2020) (Москва). Доклад: Khazetdinov, A., Aleksandrov, A., Zakiev, A., Magid, E., Hsia, K.-H. (2020). RFID-based Warehouse Management System Prototyping Using a Heterogeneous Team of Robots. Proceedings of the 23rd International Conference on Climbing and Walking Robots and Support Technologies for Mobile Machines (CLAWAR 2020), p. 263-270.
· 2020: IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA 2020) (Бангкок). Доклад: Moskvin, I., Lavrenov, R., Magid, E., Svinin, M. (2020). Modelling a Crawler Robot Using Wheels as Pseudo-Tracks: Model Complexity vs Performance. IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA 2020), p. 235-239.

Идентификаторы исследователя

ORCID: 0000-0001-7316-5664
ResearcherID: B-9697-2014
SPIN РИНЦ: 1970-8257
Google Scholar: https://scholar.google.ru/citations?user=xjBy3EcAAAAJ&hl=en
Scopus AuthorID: 7006190065

Публикации (114)

A control strategy for monitoring unknown flood regions by multiple UAVs

2026 · ARTICLE · en

This study introduces an innovative control approach for deploying multiple unmanned aerial vehicles (UAVs) to monitor an unknown food region. The proposed strategy is designed to optimally distribute UAVs across the food-afected area while cooperatively estimating the extent of inundation. To achieve this, an adaptive coverage controller is developed based on Centroidal Voronoi Tessellation (CVT), incorporating a novel mechanism for dynamically updating the density function. Within this framework, the density function serves as an evolving representation of the estimated inundation areas, allowing UAVs to adjust their positions adaptively in response to real-time environmental changes. The efectiveness of the proposed control strategy is validated through simulations conducted in the ROS/Gazebo environment, demonstrating its capability to enhance the accuracy of food monitoring and improve the spatial distribution of UAVs.

DOI ↗

Holistic Digital Human Models in Gazebo: A Case Study on Agricultural Workflows

2026 · CHAPTER · en

The agricultural sector is undergoing a digital transformation due to modern automation, robotics, sensing, and simulation technologies. This research explores a use of digital human models (DHMs) in the Gazebo virtual environment to enhance agricultural workflows, improve human-robot interaction, and ensure safety. We propose a framework that models typical agricultural scenarios, such as field mapping, harvesting efficiency control, crop inspection, obstacle avoidance, and theft detection. DHMs represent farm workers interacting with mobile autonomous systems, stationary sensors and sensor networks. The DHMs are equipped with generic and task-specific animations; the latter includes such activities as crop harvesting and field inspection. The simulation environment features agricultural settings with dynamic obstacles and predefined work zones. Performance in each scenario is proposed to evaluate using metrics such as a task’s completion time and obstacle avoidance rate. Results of preliminary simulation of the proposed simplified scenarios in the Gazebo simulator demonstrated a high potential of DHMs and Gazebo to optimize agricultural workflows and improve human-robot interaction. This study provides a foundation for leveraging simulation technologies to address practical challenges in agriculture and to support design and validation of intelligent agricultural systems.

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Agricultural Field Coverage with a Group of Mobile Robots Considering a Soil Compaction Risk and Energy Efficiency

2026 · CHAPTER · en

This article considers a dual problem of optimizing field coverage while minimizing a soil compaction and managing energy constraints of agricultural robots. The soil compaction in precision agriculture is a major challenge, as mobile robots are becoming increasingly common in field operations. A proposed optimization combines a soil compaction risk assessment with energy-efficient trajectory planning for a fleet of mobile agricultural robots. The algorithm uses a grid representation of a field, where each cell is assigned a compaction risk value using a function, which allows to cluster cells into zones with similar characteristics of the soil compaction risk. Within these zones, maximum permissible velocities of agricultural robots are determined. The Boustrophedon algorithm generates optimal coverage paths for each zone to minimize turns and ensure complete coverage. A fitness function balances multiple objectives, including soil impact, a path length, and energy constraints. To eliminate energy constraints, a genetic algorithm is used that simultaneously optimizes a placement of static charging stations and a distribution of cover paths among a tractors’ fleet. The system balances soil conservation and requirements by adapting a robot velocity to each zone. The computational experiments for various types and sizes of agricultural fields demonstrated effectiveness of the proposed approach.

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U-Net-based waterline segmentation for flood disaster response

2026 · CHAPTER · en

Floods are among the most destructive natural disasters, causing human casualties and severe economic damage. Effective monitoring of flooded areas requires automated systems capable of real-time perception and decision-making. This paper proposes a water surface segmentation model based on the U-Net architecture, trained entirely on synthetic data generated in the Gazebo simulator with variations in shoreline shape, water level, and surface color. The model demonstrated high segmentation accuracy on a test set (Dice coefficient = 0.9663, IoU = 0.9530) and maintained robustness across diverse scenarios, ranging from natural lakes to complex urban environments. When integrated into a UAV navigation algorithm, the system enabled real-time flight along detected flood boundaries. These results confirm feasibility of applying U-Net-based segmentation for UAV-assisted flood monitoring and search-and-rescue operations. Future work focuses on validating the approach with real-world data and adapting the network to resource-constrained onboard platforms.

DOI ↗

Multi-Criteria Approach to Path Planning for Unmanned Tractors Considering Energy Constraints and Soil Compaction

2026 · CHAPTER · en

Autonomous agricultural vehicles operating under the Controlled Traffic Farming (CTF) paradigm face complex routing challenges when minimizing soil compaction, total mission time, and station placement under battery constraints. This paper introduces Multi-Objective Coordinated Autonomous Routing and Placement with Fixed Lanes (MO-CARP-FL), a novel multi-objective evolutionary algorithm designed to optimize the coordinated routing of homogeneous autonomous tractors over a predefined field traffic lane. The algorithm simultaneously addresses five conflicting objectives: minimizing soil compaction using a logarithmic saturation model, minimizing total route time, reducing the number of charging stations, preserving spatial coherence in assigned routes, and balancing workload among tractors. Chromosomes encode both routing and station placement decisions, and custom crossover and mutation operators preserve structural feasibility. A soil compaction model and energy-aware constraints are integrated into the evaluation function. Experimental simulations demonstrate that MO-CARP-FL produces environmentally sensitive routing plans while reducing field degradation. The proposed method is validated through CTF field scenarios, and its results are visualized to provide interpretable insights into route distribution, station usage, and soil impact. This work contributes to multi-objective optimization in agricultural logistics by addressing both environmental impact and operational efficiency in autonomous field operations.

DOI ↗

Closed-Loop Chain Linkage-Based Hand Exoskeleton: A Lightweight and Modular Solution for Hand Rehabilitation

2026 · CHAPTER · en

Prosthetic hands are vital assistive devices that significantly enhance quality of life for individuals with upper limb amputations, enabling them to regain autonomy and perform essential daily activities. However, many existing prosthetic solutions are hindered by high costs, excessive weight, and complex actuation systems that limit accessibility and usability. This paper introduces a novel prosthetic hand design that addresses these limitations through a mechanically efficient and cost-effective approach. The proposed system employs five motors, one per finger, combined with a closed-loop chain linkage mechanism that transmits motion across joints of each finger. This eliminates a need for multiple actuators per finger, thereby reducing an overall weight, power consumption, and cost of the device. We present a complete design methodology, a mechanical architecture, and functional analysis of the prototype. The mechanical structure achieves finger flexion up to 125 degrees, distal interphalangeal (DIP) joint articulation up to 90 degrees, and wrist deviation of ±20 degrees, closely mimicking natural hand movement. The results demonstrate feasibility and advantages of the approach, offering a promising direction for developing affordable, efficient, and user-friendly prosthetic hands.

DOI ↗

Hidden Markov Prediction and Fuzzy Control Obstacle Avoidance for Submarine Robot

2026 · CHAPTER · en

This paper introduces a novel obstacle avoidance strategy for an underwater robot, synergistically integrating Hidden Markov Chains (HMC) with a Mamdani Fuzzy inference controller. The HMC forecasts a vector of future states, and the maximum a posteriori state probabilities derived from this prediction directly inform the control actions of the fuzzy system. The proposed fuzzy logic controller employs five input variables: the HMC’s predicted robot state (represented as crisp sets), instantaneous linear velocity, underwater depth, and yaw and pitch angular velocities. The fuzzy controller generates three output variables, which directly command the robot’s actuators: the propulsion motor, the yawing motor, and the ballasting system, the latter operating via an integrated hydraulic piston mechanism. Furthermore, this work develops dynamics-based models for the robot’s propulsion, steering, and ballasting subsystems, complemented by sensor fusion models designed to provide real-time control feedback. The paper also details the robot’s platform and its underlying system architecture, engineered to support multi-threaded, real-time control operations. Experimental and simulation results are presented to validate the efficacy of the proposed obstacle avoidance strategy, demonstrating its robustness in challenging underwater locomotion scenarios.

DOI ↗

Camera-based safety system for collaborative assembly

2025 · ARTICLE · en

Collaborative assembly represents one of the most prevalent practical applications of collaborative robots in intelligent manufacturing. Developing intelligent systems to ensure safety of collaborative assembly processesrequires a special attention. In this work, we introduce a visual safety system designed to monitor hazardous situations that may occur during collaborative assembly, potentially resulting in operator injuries. Unlike many other vision-based systems, we solely rely on data from two RGB cameras, without acquiring additional depth information from other sensors. These cameras provide top and side projections of a collaborative workspace. The safety system assesses a current level of a risk by employing two neural network YOLOv8-cls models. These models are pretrained on the ImageNet dataset and subsequently fine-tuned on our dataset. Upon identifying a potential hazard, the system employs our proposed algorithm to determine whether to slow down or halt a robot’s motion. Additionally, the system integrates with a visual control system that utilizes an operator gesture control throughout an assembly process. We further conduct experiments to compare our system’s assessment with an assessment of human experts. An analysis of the experiments demonstrated a high level of correlation between the evaluations of the autonomous system and the human experts. Benefits of the proposed system encompass its relative cost-effectiveness and ease of setup.

DOI ↗

Double spiraliform path planning and tracking for agricultural mobile robotics: A modeling and simulation study

2025 · ARTICLE · en

This research presents a comprehensive study on the design and implementation of a robust trajectory tracking system for autonomous agricultural robots. It introduces a unified kinematic model that integrates different rolling structures, facilitating performance across various robotic designs. The novel path planning method utilizes double spiraliform tracks to enhance movement efficiency in complex agricultural settings and generate flexible fields in terms of scale, orientation, and location, providing reference trajectory models. A sliding mode controller is developed to manage nonlinear dynamics and discontinuous input references, ensuring stability and precision during operation. The sliding approach was compared against four controllers: a linear feedback controller, a state-space feedback controller, a proportional controller, and a proportional–integral controller. The evaluation of accuracy and precision with respect to the input reference model showed similar performances across the controllers. However, the sliding approach proved superior when inputting nonlinear reference and discontinuous external perturbations, producing chattering metric errors averaging 0.94 m and mean = 0.012 m, for components, respectively A Lyapunov analysis confirmed the sliding mode controller stability during path tracking nonlinear dynamics, handling unpredictable operational conditions. Numerical simulations validated the controller’s effectiveness, showcasing its robustness against external disturbances and its ability to maintain stability and precision during operation.

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LIRS-USim: a Gazebo-based Tool for Modeling Urban Environments and Sensory Data Uncertainties

2025 · ARTICLE · en

Urban Search and Rescue (USAR) robotics deals with emergent situations that occur in urban environments due to natural and human-made disasters. To support early stages of algorithms’ testing and evaluation, we developed an easy to use USAR simulation tool (LIRS-USim) that models typical USAR missions within the Gazebo simulator. The proposed robot operating system based tool is capable of modeling a virtual environment with hazardous zones, constructing a 3D Gazebo world from an arbitrary 2D image and populating it with various obstacles from the Gazebo library, simulating uncertainties and failures of robot’s onboard sensors. To set up a hazardous zone, its location, size and a radiation or chemical contamination shape are defined by a user. Next, any existing in Gazebo robot model with any onboard sensors could be loaded into the 3D world, and probabilities of each sensor uncertainty and failure could be set individually by a user. Moreover, LIRS-USim allows loading several robots of different types into a single Gazebo world and further monitor each robot and each sensor. LIRS-USim was successfully tested with Husky, Warthog, Jackal, and Hector Quadrotor standard robot models. The source code of LIRS-USim is available for free academic use.

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Курсы (2)

Человеко-машинное взаимодействие

2022/2023 · Магистратура · рус
Проектно-исследовательский семинар

2021/2022 · Магистратура · рус