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Welcome to the Mobile Robotics & Olfaction Lab

Our research focuses on perception for intelligent systems, in particular for mobile robots. Our goal is to advance the theoretical and practical foundations that allow mobile robots to operate in an unconstrained, dynamic environment. The approaches that we develop address real-world needs and are typically characterized by fusion of different sensor modalities. Where possible, the results of our research work are timely integrated in industrial demonstrators.

Featured Publications (2020)

  • M. A. Arain, V. Hernandez Bennetts, E. Schaffernicht, and A. J. Lilienthal.
    Sniffing Out Fugitive Methane Emissions: Autonomous Remote Gas Inspection with a Mobile Robot.
    International Journal of Robotics Research (IJRR), 2020
    BibTeX | DiVA | URL ]
  • J. Burgues, V. Hernandez Bennetts, A. J. Lilienthal and S. Marco.
    Gas Distribution Mapping and Source Localization Using a 3D Grid of Metal Oxide Semiconductor Sensors.
    Sensors and Actuators. B, Chemical (SAB), 304, 127309, 2020
    BibTeX | DiVA | URL ]
  • R. T. Chadalavada, H. Andreasson, M. Schindler, R. Palm, and A. J. Lilienthal.
    Bi-directional navigation intent communication using spatial augmented reality and eye-tracking glasses for improved safety in human–robot interaction.
    Robotics and Computer-Integrated Manufacturing (RCIM), 2020
    BibTeX | DiVA | URL ]
  • T. P. Kucner, M. Magnusson, L. Palmieri, C. S. Swaminathan, and A. J. Lilienthal.
    Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots.
    Springer Cognitive Systems Monographs (COSMOS), Volume 42, 2020
    BibTeX | DiVA | URL ]
  • Q. Liao, D. Sun, H. Andreasson.
    Point Set Registration for 3D Range Scans Using Fuzzy Cluster-based Metric and Efficient Global Optimization.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2020
    BibTeX | DiVA | URL | PDF ]
  • A. Rudenko, T. P. Kucner, C. S. Swaminathan, R. T. Chadalavada, K. O. Arras and A. J. Lilienthal.
    THÖR: Human-Robot Navigation Data Collection and Accurate Motion Trajectories Dataset.
    IEEE Robotics and Automation Letters (RA-L), 5(2):676-682, 2020
    BibTeX | DiVA | URL ]
  • A. Rudenko, L. Palmieri, M. Herman, K. M. Kitani, D. M. Gavrila and K. O. Arras.
    Human Motion Trajectory Prediction: A Survey.
    International Journal of Robotics Research (IJRR), 39(8):895-935, 2020
    BibTeX | DiVA | URL ]

Featured Publications (2017)

  • T. P. Kucner, M. Magnusson, E. Schaffernicht, V. M. Hernandez Bennetts and A. Lilienthal. Enabling Flow Awareness for Mobile Robots in Partially Observable Environments. IEEE Robotics and Automation Letters 2017BibTeX | DiVA  ]
  • V. Hernandez Bennetts, T. P. Kucner, E. Schaffernicht, P. P. Neumann, H. Fan and A. J. Lilienthal. Probabilistic Air Flow Modelling Using Turbulent and Laminar Characteristics for Ground and Aerial Robots. IEEE Robotics and Automation Letters, 2017BibTeX | DiVA  ]

Featured Publications (2015)

  • R. Krug, T. Stoyanov and A. Lilienthal. Grasp Envelopes for Constraint-based Robot Motion Planning and Control. In Robotics: Science and Systems Conference: Workshop on Bridging the Gap between Data-driven and Analytical Physics-based Grasping and Manipulation 2015BibTeX | DiVA  | PDF ]

 

 
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