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.
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
In the European project EUROBENCH, we are developing a framework for benchmarking the performances of bipedal systems: from humans to humanoids through wearable robots. Fair benchmarking requires defining and sharing clear and complete protocols so that bipedal systems can be studied and compared within similar and reproducible conditions. Even if the experimental methods and system comparisons are common scientific tasks, the description of the experimental protocols that are followed are rarely complete enough to allow it to be replicated. We list, in this article, the information required to properly define a protocol (e.g. experiment objectives, testbeds, type of collected and processed data, performance indicators used to score and compare experiments). Agreeing on a common terminology for benchmarking concepts will ease the evaluation of new technologies and promote communication between the different stakeholders involved in the development and use of bipedal systems
This article deals with the 2D image-based recognition of industrial parts. Methods based on histograms are well known and widely used, but it is hard to find the best combination of histograms, most distinctive for instance, for each situation and without a high user expertise. We proposed a descriptor subset selection technique that automatically selects the most appropriate descriptor combination, and that outperforms approach involving single descriptors. We have considered both backward and forward mechanisms. Furthermore, to recognize the industrial parts a supervised classification is used with the global descriptors as predictors. Several class approaches are compared. Given our application, the best results are obtained with the Support Vector Machine with a combination of descriptors increasing the F1 by 0.031 with respect to the best descriptor
This paper is related to the observation of human operator manipulating objects for teaching a robot to reproduce the action. Assuming the robotic system is equipped with basic manipulation skills, we focus here on the automatic segmentation of the observed manipulation, for extracting the relevant key frames in which the manipulation is best described. The segmentation method proposed is based on the instantaneous work, and presents the advantage of not depending on the force and pose sensing locations. The experimentations concern two different manipulation skills, sliding and folding. We demonstrate in different settings that such segmentation method is efficient.
Detection and description of keypoints from an image is a well-studied problem in Computer Vision. Some methods like SIFT, SURF or ORB are computationally really efficient. This paper proposes a solution for a particular case study on object recognition of industrial parts based on hierarchical classification. Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical classification is looking for. We demonstrate that this method performs better than using just one method like ORB, SIFT or FREAK, despite being fairly slower.
This paper describes a tool for generating ROS packages and nodes. Compared to the relatively basic traditional package creation method, this tool can generate a whole node structure, including its life-cycle and the exposed interface to other ROS nodes. Following a separation of concerns, the developer only defines the interaction means in a XML file, and the tool provides the whole skeleton of the nodes, including the interface creation and management. This way, the developer can focus on his real added value, the implementation of the node logic. Compared to advanced node management frameworks proposed in literature, the tool proposed does not require the developer to understand and agree on complex high-level architecture models. The developer only has to select a template model, and to provide the desired interface to get the code generated. The package generation is made possible thanks to package templates, and we provide with the generator tool two templates for creating nodes either in C or Python. The user has also the possibility to design his own template, so that he can develop the one that best fits his needs and best practices. The package generator code is accessible on public repository hosting facilities.