جست‌وجوی استاد و پژوهشگر

Francois Chaumetteمشاهده پروفایل

استاد پژوهشی

• Robotics
• Computer Vision
• Visual Servoing
• +۱۷ مورد دیگر

François Chaumette is a Senior Research Scientist (Directeur de recherche) at Inria, affiliated with IRISA and the Centre Inria de l'Université de Rennes. He has been a key researcher in robotics and computer vision since 1990 and led the Lagadic research team from 2004 to 2017. His research interests are centered on robot vision, particularly visual servoing and active perception . He has made foundational contributions to image-based and position-based visual servoing, and his work integrates control theory, computer vision, and robotics. His research spans applications in mobile robotics, aerial systems, medical robotics, space robotics, and soft object manipulation. The recent publications highlight a consistent focus on visual servoing under complex constraints—such as motion blur, occlusions, and deformations—applied to drones, cable-driven robots, and space systems. There is a strong emphasis on robustness , stability analysis , and hybrid sensing (e.g., vision + proximity, vision + force). His work with the RemoveDebris mission demonstrates real-world impact in space robotics. AFCET/CNRS Prize for best Ph.D. in Automatic Control Best paper awards at RFIA 1996 & 2004 Best paper in IEEE T-RA (2002) Best paper in IEEE RA-L (2019) Best paper in IEEE RAM (2020) IEEE Fellow (2013) He has advised over 30 Ph.D. students, many of whom have become active researchers in robotics. He has served in editorial roles for top journals including IEEE Transactions on Robotics , IEEE Robotics and Automation Letters , and the International Journal of Robotics Research . He was elected to the IEEE RAS Administrative Committee (2016–2018) and served on ERC grant panels for robotics. Chaumette is the main developer of ViSP (Visual Servoing Platform), a widely used C++ library for visual tracking and servoing. His leadership in both theoretical advances and software tools has significantly shaped the visual servoing community.

Marc Gouttefardeمشاهده پروفایل

پژوهشگر

• Cable-Driven Parallel Robots
• Robotics
• Mechatronics
• +۵ مورد دیگر

Marc Gouttefarde is a CNRS Senior Researcher (DR2) at LIRMM (Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier), part of University of Montpellier. He leads the Robotics Department at LIRMM and serves as Scientific Advisor for Robotics at CNRS Informatics. His research focuses on cable-driven parallel robots, with significant contributions to workspace analysis, robot design, control systems, and practical applications. His research interests center on cable-driven parallel robots (CDPRs), with expertise in workspace analysis, design optimization, motion planning, and control systems. Gouttefarde pioneered the CoGiRo cable configuration that enables large workspace to footprint ratios, demonstrated in the CoGiRo prototype capable of handling 300+ kg payloads. His work spans multiple applications including marine litter removal, building facade construction, and industrial manufacturing. He has developed methodologies for determining smallest maximum cable tension and contributed to vibration analysis and damping techniques for cable robots. His recent publications show a strong trend toward underwater applications of cable-driven robots, particularly for marine environmental remediation. The MAELSTROM project's robotic seabed cleaning platform represents a significant practical application of his research. Additional trends include hybrid actuation systems combining cables with thrusters, advanced control strategies for pick-and-throw applications, and optimization of cable routing for reconfigurable systems. His work consistently bridges theoretical analysis with practical implementation through numerous demonstrators. Crossley Best Paper Award for 'Discrete reconfiguration planning for Cable-Driven Parallel Robots' Gouttefarde has coordinated multiple significant research projects including the ANR CoGiRo project that developed the large-dimension CDPR prototype, the DexterWide ANR project demonstrating coordinated motion of CDPRs with on-board manipulators, and the HEPHAESTUS EU project for curtain wall installation. He currently participates in the ANR CABTIVE project on 3D printing with cable robots and the AAutonom project for agricultural applications. His leadership extends to coordinating the 'Robotique Centrée sur l'Humain' initiative supported by Région Occitanie. As Head of LIRMM Robotics Department, Gouttefarde oversees one of France's leading robotics research groups. His team, the DEXTER team, focuses on cable-driven parallel robots and their applications. The group has developed multiple demonstrators including the CoGiRo robot, the robotic seabed cleaning platform for marine litter removal, and systems for building facade construction. Their research bridges theoretical analysis with practical implementation, consistently validating theoretical results through physical prototypes.

Jacques Gangloffمشاهده پروفایل

استاد

• Robotics
• Medical Robotics
• Vision-Based Control
• +۵ مورد دیگر

Jacques Gangloff is a Full Professor at Télécom Physique Strasbourg (University of Strasbourg) and a member of the ICube Laboratory. He holds roles such as Co-director of the IRIV Master’s program (since 2015), Head of the AR course in IRIV Master (since 2005), and Chairman of the Scientific Expert Committee of Télécom Physique Strasbourg (since 2022). His research focuses on robotics, medical robotics, and vision-based control systems. He earned his PhD in 1999 and Habilitation in 2004. He is an Associate Editor of IEEE Robotics and Automation Letters (since 2024). Education: Engineering degree from INSA Strasbourg (1992), DEA in Photonics and Imaging (1996), Agrégation in Electrical Engineering (1995). Research Themes: Medical Robotics, Predictive Control, Frugal Robotics, and Complex Systems. Awards: Multiple best paper awards in robotics and medical robotics conferences. He leads the 'Complex Systems and Sparsity' theme in the RDH team and has developed software tools like RPIt and MGPC for control systems. His teaching includes courses on robotics, real-time computing, and drones.

• Event-Driven Control
• Cyber-Physical Systems
• Robotics
• +۶ مورد دیگر

Sylvain Durand Chamontin serves as an Associate Professor at INSA Strasbourg, affiliated with the ICube research laboratory (UMR 7357) and the AVR (Automation, Vision, Robotics) team. His teaching encompasses advanced automation (anti-windup, Smith predictor, LQ control), embedded systems/IoT, motorization/axis control, linear automation (state feedback, observers), and sequential automation (GRAFCET, GEMMA) for electrical engineering, mechatronics, and mechanical engineering students across 2nd–5th year programs. His research centers on frugal design and control of embedded cyber-physical/robotic systems under resource constraints, with a dedicated focus on non-periodic sampling and event-driven techniques . Key domains include event-driven control architectures, dynamic vision sensor-based visual servoing, aerial robotics (UAVs/aerial manipulators), and swarm robotics. This work systematically reduces computational load, communication overhead, and energy consumption while maintaining robust performance in resource-limited environments—critical for embedded implementations in drones and cyber-physical systems. Analysis of Durand's 15 most recent publications (2022–2025) reveals a dominant trend in event-driven control for robotics, increasingly integrating machine learning for adaptive tuning. His work targets practical applications in aerial robotics, including UAV stabilization under ground effects, elastic-suspension aerial manipulation, and event-based visual servoing. A strong emphasis on frugality permeates techniques like non-periodic sampling and resource-aware control strategies, directly addressing hardware limitations in embedded platforms. Durand mentors award-winning PhD students including M. Pivert (Best Student Paper Award, IFAC Robotics 2025), T. Paul (i-PhD Innovation Contest 2022), and A. Yiğit (Best PhD Award in French Robotics 2021). He leads multiple ANR-funded projects: e-VISER (event-driven visual control, 2018–2021), DexterWide (cable robots, 2015–2018), and current initiatives eSWARM (modular UAVs, 2023–2025), muteSWARM (acoustic swarm control, 2023–2027), STRAD (street art drone, 2022–2026), TIR4sTREEt (urban micro-climatology, 2022–2026), and dark-NAV (GPS-denied navigation, 2021–2025). Within ICube's AVR team, Durand drives laboratory development of the dextAIR robot (omnidirectional aerial manipulator with elastic suspension) and embedded control systems for cable-driven parallel robots and swarm robotics. His experimental work emphasizes real-time implementation, energy efficiency, and frugal engineering principles—translating theoretical event-driven control into hardware solutions for resource-constrained robotic applications.

• Medical Robotics
• Soft Robotics
• Surgical Robotics
• +۳ مورد دیگر

Olivier Piccin is a Lecturer at INSA Strasbourg, affiliated with the Automatic Vision and Robotics team at the LSIIT (CNRS & University of Strasbourg). He holds a DEA in Robotics from Paris-6 University and a doctoral thesis from LAAS in Toulouse. His roles include teaching in mechanical engineering and mechatronics, as well as administrative leadership positions such as Mechanical Platform Manager at INSA. Research focuses on medical robotics, particularly in interventional radiology and minimally invasive surgery, with contributions to soft robotics, robotic control systems, and surgical tool design. Education: National School of Arts and Crafts (Arts&Métiers ParisTech), 1989–1992 DEA in Robotics, Paris-6 University, 1991–1992 Doctoral Thesis, LAAS, Toulouse, 1992–1995 Research Interests: Medical robotics, soft robotics, surgical robotics, robotic control systems, and biomedical engineering. His work advances applications in minimally invasive surgery and robotized medical devices, leveraging material science and advanced control theory. Key Contributions: Over 30 publications since 2005, including studies on cable-driven robotics, soft actuator fabrication, and haptic feedback systems for surgical tools. Active collaboration with IRCAD’s medical robotics platform. Administration: Mechanical Platform Manager (since 1999) Elected member of LGeCo lab council (2005–2008) INSA Board of Directors member (2007–2011) Labs/Teams: Automatic Vision and Robotics team at LSIIT, collaborating with IRCAD’s medical robotics platform for surgical innovation.

• robotic manipulation
• robot learning
• motion planning
• +۳ مورد دیگر

Dmitry Berenson is an Associate Professor in the Robotics Department at the University of Michigan, Ann Arbor. Previously, he served as an Assistant Professor at Worcester Polytechnic Institute from 2012 to 2016, following a postdoctoral position at the University of California, Berkeley in 2011-2012. His educational background includes: B.S. in electrical engineering from Cornell University (2005) Ph.D. in robotics from the Robotics Institute, Carnegie Mellon University (2011) Dr. Berenson's research focuses on advancing robotic manipulation capabilities, particularly in challenging scenarios involving deformable objects and complex environments. His work bridges the gap between theoretical motion planning algorithms and practical robotic applications, with emphasis on developing methods that can handle uncertainty, occlusion, and complex physical interactions. He has made significant contributions to contact-rich manipulation, deformable object handling, and the integration of learning with classical planning approaches. His research has important applications in manufacturing, agriculture, surgery, and everyday human environments where robots need to interact with complex objects. His recent publications demonstrate a strong trend toward integrating machine learning techniques (particularly diffusion models and other deep learning approaches) with traditional motion planning and manipulation methods. This hybrid approach allows for more robust handling of complex scenarios like deformable object manipulation, occluded environments, and long-horizon tasks that have traditionally challenged robotics systems. Among his notable achievements, Dr. Berenson has received the prestigious IEEE RAS Early Career Award and the NSF CAREER award, recognizing his significant contributions to robotics research and education. As an academic advisor, Dr. Berenson has mentored numerous students who have gone on to contribute to the field of robotics. His research has been supported by various grants that have enabled his team to pursue innovative approaches at the intersection of motion planning, manipulation, and machine learning. His work often involves interdisciplinary collaboration across computer science, mechanical engineering, and applied mathematics. Dr. Berenson leads a research group at the University of Michigan focused on robotic manipulation and motion planning. His lab develops algorithms that enable robots to perform complex manipulation tasks in unstructured environments, with particular expertise in handling deformable objects and reasoning about physical interactions. The group maintains strong connections with industry partners and other academic institutions, fostering a collaborative environment for advancing the state of the art in robotics.

• Mechanical Design
• Robotics
• Uncertainty Modeling
• +۶ مورد دیگر

Nicolas Binaud is a Lecturer at Paul Sabatier University (UPS), where he is a member of the Modeling of Mechanical Systems and Microsystems group (MS2M) at Espace Clément Ader in Toulouse, France. His research focuses on multidisciplinary design in uncertain environments with emphasis on robustness, reliability, and sensitivity analysis of mechanical systems. His research interests span across: Multidisciplinary design under uncertainty Modeling of uncertainties and variations of design variables Sensitivity analyses for mechanical systems Development of performance indices for preliminary design Mechanical and computer-aided design Digital tools for mechanics Probability and reliability engineering Dr. Binaud's scholarly work demonstrates expertise in mechanical systems design with particular strength in cable-driven parallel robots, structural reliability, and predictive maintenance. His research shows strong interdisciplinary connections between mechanical engineering, aerospace applications (particularly airframe maintenance), and materials science (especially electrostatic interactions in microsystems). Analysis of his publication record reveals consistent output with recent work focusing on sensitivity analysis of robotic systems and electrostatic characterization techniques. His notable contributions include: Development of comprehensive methods for sensitivity analysis of cable-driven parallel robots Research on model-based prognostics for fatigue crack growth in aircraft structures Studies on 3D charge localization in thin dielectric materials using atomic force microscopy Applications of Kalman filtering techniques for structural health monitoring Cost-driven optimization of predictive maintenance policies for aerospace structures

Hadrien Courtecuisseمشاهده پروفایل

پژوهشگر

• Medical Robotics
• Real-Time Simulations
• Finite Element Methods
• +۳ مورد دیگر

Dr. Hadrien Courtecuisse is a Researcher (Chargé de Recherche) at CNRS, affiliated with the AVR/ICube team in Strasbourg since 2013. He holds a Ph.D. in Computer Science from Inria (2011), specializing in parallel architectures for medical simulations. His postdoctoral work at Cardiff University (2012) focused on biomechanical modeling of soft tissues. He later contributed to the Institut Hospitalo-Universitaire (IHU) as a research engineer. His expertise spans sparse linear algebra, real-time simulations, GPU computing, and medical robotics, particularly in surgical training systems and robotic control using inverse finite element models. Education: Ph.D., SHAMAN Team, Inria (2011) Postdoctoral Research, IMAM, Cardiff University (2012) Research Interests: Courtecuisse’s work emphasizes real-time computational methods for medical applications, including deformable object simulation, haptic feedback, and robotic assistance. He develops algorithms for contact response, topological changes, and parallel computing to enhance surgical training and robotic precision. His contributions address challenges in needle insertion, soft tissue interaction, and real-time error control in surgical simulations. Awards & Recognition: No specific scientific awards mentioned. Key Projects: MIMESIS Project (Inria): Focuses on medical robotics and real-time simulation for therapy planning. SOFA-FrameWork: Contributed to open-source simulation software for deformable objects and haptics. Calipso: Image editing via physics-based CAD models. Labs & Teams: Active in the AVR/ICube team at CNRS, collaborating with Inria and international institutions like Cardiff University.