Publications

In this paper, we present a low-cost and highly configurable quality inspection system capable of capturing 2.5D color data, created using off-the-shelf machine vision components, open-source software libraries, and a combination of standard and novel algorithms for 2.5D data processing. The system uses laser triangulation to capture 3D depth, in parallel with a color camera and a line light projector to capture color texture, which are then combined into a color 2.5D model in real-time. Using many examples of completeness inspection tasks that are extremely difficult to solve with current 2D-based methods, we demonstrate how the 2.5D images and point clouds generated by our system can be used to solve these complex tasks effectively and efficiently. Our system is currently being integrated into a real production environment, showing that completeness inspection incorporating 3D technology can be readily achieved in a short time at low costs. © 2013 Elsevier B.V. All rights reserved.

Motion perception and classification are key elements exploited by humans for recognizing actions. The same principles can serve as a basis for building cognitive architectures which can recognize human actions, thus enhancing challenging applications such as human robot interaction, visual surveillance, content-based video analysis and motion capture. In this paper, we propose an autonomous system for real-time human action recognition based on 3D motion flow estimation. We exploit colored point cloud data acquired with a Microsoft Kinect and we summarize the motion information by means of a 3D grid-based descriptor. Finally, temporal sequences of descriptors are classified with the Nearest Neighbor technique. We also present a newly created public dataset for RGB-D human action recognition which contains 15 actions performed by 12 different people. Our overall system is tested on this dataset and on the dataset used in Ballin, Munaro, and Menegatti (2012), showing the effectiveness of the proposed approach in recognizing about 90% of the actions. © 2013 Elsevier B.V.

This paper describes our experience in the simulation of humanoid soccer robots using two general purposes 3D simulators, namely USARSim and Microsoft Robotics Studio. We address the problem of the simulation of a soccer match among two teams of small humanoid robots in the RoboCup Soccer Kid-Size Humanoid competitions. The paper reports the implementation of the virtual models of the Robovie-M humanoid robot platform in the two simulators. Robovie-M was the robot used by our team “Artisti” in the RoboCup 2006 competitions. This paper focuses on the procedures needed to implement the virtual models of the robot and in the details of the models. We describe experiments assessing the feasibility and the fidelity of the two simulators. © 2008 World Scientific Publishing Company.