3D visual sensing of human hand for remote operation of a robotic hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

3D Maps Representation Using GNG

Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D map reconstruction, but the storage and processing of the incremental data provided by the different sensors through time quickly become unmanageable. In this work, we focus on 3D maps representation and propose the use of the Growing Neural Gas (GNG) network as a model to represent 3D input data. GNG method is able to represent the input data with a desired amount of neurons or resolution while preserving the topology of the input space. Experiments show how GNG method yields a better input space adaptation than other state-of-the-art 3D map representation methods.

Presence of Siloxanes in the Biogas of a Wastewater Treatment Plant Separation in Condensates and Influence of the Dose of Iron Chloride on its Elimination

The siloxanes present in the biogas produced during anaerobic digestion damage the mechanism of cogeneration equipment and, consequently, negatively affect the energy valorization process. For this reason, the detection and elimination of these silicon-derived chemical compounds are a priority in the management of cogeneration facilities. In this regard, the objectives of this paper are, firstly, to characterize the siloxanes in the biogas and, secondly, to qualitatively evaluate the influence of the dose of iron chloride on its elimination. The research was performed at the Rincón de León Wastewater Treatment Plant (Alicante, Spain). The outflow biogas of the digesters and of the pressurized gasometers was sampled and analyzed. The results obtained made it possible to demonstrate, firstly, the absence of linear siloxanes and that, of the cyclic siloxanes, the predominant type was decamethylcyclopentasiloxane, and, secondly, that the addition of iron chloride in the digesters significantly reduces the siloxane content in the biogas. Additionally, it was demonstrated that the process of compression of the biogas, with the elimination of condensates, also produces significant reductions in the concentration of siloxanes in the biogas.