Anthony Remazeilles

Anthony Remazeilles

Senior researcher


Health Division, Medical Robotic


I am a researcher and project manager at Tecnalia, Donostia, in the Spanish basque country. I work in the Medical Robotics group, from the Health Division, as well as in the Advanced Manufacturing group of the Industry and Transport Division. I am involved in the development of technological solutions for physical Human Robot interaction, vision-based robotic manipulation, … I am also very interested in software architecture, within (or without) the ROS framework.


  • Visual servoing
  • Computer vision
  • Surgical Robotics
  • Software architecture


  • PhD in Computer Science, 2004

    Université de Rennes I

  • Master of Research in Image and Artificial Intelligence, 2001

    Université de Rennes I

  • Engineer Degree in Computer Science, 2001

    INSA of Rennes

















Assistive Robotics (2010-2013)


Vision-based wheelchair control (2008-2009)

Visual servoing

Work conducted at IRISA (2001-2006)


a robotic butler for injured people (2006-2008)

Recent Publications

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Minimum Cost Averaging for Multivariate Time Series Using Constrained Dynamic Time Warping: A Case Study in Robotics

In this paper, an innovative algorithm for averaging a set of multivariate time series with different lengths based on Constrained Dynamic Time Warping (CDTW) is proposed. This approach relies on the CDTW to provide the non-linear alignment of the multivariate time series, and employs the proposed Minimum Cost Averaging (MCA) technique to identify the optimum matches and get equal-length time series. MCA-CDTW is a task-agnostic approach that after selecting a reference curve, transforms the rest of the demonstrations in the set to obtain new curves that are time-aligned with the reference. From these transformed curves, not only the mean but also the signal variability can be directly extracted. This technique provides smooth mean curves even when there are large deviations between the demonstrations in the set, and still the complexity of the proposed algorithm is significantly reduced compared to other averaging techniques from the literature. When learning techniques are used to teach a motion to a robotic system, obtaining smooth trajectories is important to achieve good robotic behaviors. The new algorithm MCA-CDTW is tested and compared on two different databases: a literature database where humans move a robotic arm with kinaesthetic teaching, and a set of recordings of a teleoperated robotic arm performing laboratory manipulation. On both datasets, it is demonstrated that the new approach is providing smooth average trajectories.

Making Bipedal Robot Experiments Reproducible and Comparable: The Eurobench Software Approach

This study describes the software methodology designed for systematic benchmarking of bipedal systems through the computation of performance indicators from data collected during an experimentation stage. Under the umbrella of the European project Eurobench, we collected approximately 30 protocols with related testbeds and scoring algorithms, aiming at characterizing the performances of humanoids, exoskeletons, and/or prosthesis under different conditions. The main challenge addressed in this study concerns the standardization of the scoring process to permit a systematic benchmark of the experiments. The complexity of this process is mainly due to the lack of consistency in how to store and organize experimental data, how to define the input and output of benchmarking algorithms, and how to implement these algorithms. We propose a simple but efficient methodology for preparing scoring algorithms, to ensure reproducibility and replicability of results. This methodology mainly constrains the interface of the software and enables the engineer to develop his/her metric in his/her favorite language. Continuous integration and deployment tools are then used to verify the replicability of the software and to generate an executable instance independent of the language through dockerization. This article presents this methodology and points at all the metrics and documentation repositories designed with this policy in Eurobench. Applying this approach to other protocols and metrics would ease the reproduction, replication, and comparison of experiments.