Robotic Ironing with 3D Perception and Force/Torque Feedback in Household Environments

As robotic systems become more popular in household environments, the complexity of required tasks also increases. In this work we focus on a domestic chore deemed dull by a majority of the population, the task of ironing. The presented algorithm improves on the limited number of previous works by joining 3D perception with force/torque sensing, with emphasis on finding a practical solution with a feasible implementation in a domestic setting. Our algorithm obtains a point cloud representation of the working environment. From this point cloud, the garment is segmented and a custom Wrinkleness Local Descriptor (WiLD) is computed to determine the location of the present wrinkles. Using this descriptor, the most suitable ironing path is computed and, based on it, the manipulation algorithm performs the force-controlled ironing operation. Experiments have been performed with a humanoid robot platform, proving that our algorithm is able to detect successfully wrinkles present in garments and iteratively reduce the wrinkleness using an unmodified iron.Comment: Accepted and to be published on the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017) that will be held in Vancouver, Canada, September 24-28, 201

Information Management for Multi-Agent Systems

Multi-Agent Systems (MAS) are becoming increasingly popular in large-scale dynamic domains such as Smart Cities and Search \& Rescue (S\&R) missions. In order for agents to cooperate efficiently in such domains, they need to distribute tasks, share knowledge, resolve conflicts, incorporate unknown agents, assign roles among each other, assign and keep track of teams of agents, etc. The cooperation in such dynamic domains requires both a software platform that supports the interoperability of cyber-physical agents as well as a shared Knowledge Base that stores general semantic information about the entities of discourse as well as live status information. ALICA, which is an in-house Multi-Agent platform, addresses such domains and is well suited to tackle a lot of these problems. To further enhance its capabilities, an extension is planned in order to integrate the standardised context information interface NGSI-LD as well as the widely used FIWARE models and components for Smart Cities, which enables the management of static and dynamic context information in normal and crisis situations

Going Further with Point Pair Features

Point Pair Features is a widely used method to detect 3D objects in point clouds, however they are prone to fail in presence of sensor noise and background clutter. We introduce novel sampling and voting schemes that significantly reduces the influence of clutter and sensor noise. Our experiments show that with our improvements, PPFs become competitive against state-of-the-art methods as it outperforms them on several objects from challenging benchmarks, at a low computational cost.Comment: Corrected post-print of manuscript accepted to the European Conference on Computer Vision (ECCV) 2016; https://link.springer.com/chapter/10.1007/978-3-319-46487-9_5