This paper presents a complete and original calibration framework for the three-CCD polarimetric cameras. These Division-of-Amplitude imaging polarimeters provide polarization images in real-time and open new applications in robotics. In order to fully exploit properties from polarization images, the sensor has to be calibrated leading sometimes to a tedious task that has to be undertaken with specific optical devices in a controlled environment. The proposed framework relies only on the use of a tablet and enables both to calibrate the geometric and the polarization settings of the camera. After rotating freely by hand the tablet in front of the camera, the system is automatically calibrated providing both the well-known geometric calibration matrix as well as the polarization calibration matrix. The last one is derived from the estimation of the orientation of the three polarizers, and the estimation of their relative values of degree of polarization and average transmittance.

This review article aims to address common research questions in passive polarized vision for robotics. What kind of polarization sensing can we embed into robots? Can we find our geolocation and true north heading by detecting light scattering from the sky as animals do? How should polarization images be related to the physical properties of reflecting surfaces in the context of scene understanding? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying future directions in passive polarized vision for robotics. After an introduction, three key interconnected areas will be covered in the following sections: embedded polarization imaging; polarized vision for robotics navigation; and polarized vision for scene understanding. We will then discuss how polarized vision, a type of vision commonly used in the animal kingdom, should be implemented in robotics; this type of vision has not yet been exploited in robotics service. Passive polarized vision could be a supplemental perceptive modality of localization techniques to complement and reinforce more conventional ones.

Polarimetric imaging has been applied in a growing number of applications in robotic vision (ex. underwater navigation, glare removal, de-hazing, object classification, and depth estimation). One can find on the market RGB Polarization cameras that can capture both color and polarimetric state of the light in a single snapshot. Due to the sensor's characteristic dispersion, and the use of lenses, it is crucial to calibrate these types of cameras so as to obtain correct polarization measurements. The calibration methods that have been developed so far are either not adapted to this type of cameras, or they require complex equipment and time consuming experiments in strict setups. In this letter, we propose a new method to overcome the need for complex optical systems to efficiently calibrate these cameras. We show that the proposed calibration method has several advantages such as that any user can easily calibrate the camera using a uniform, linearly polarized light source without any a priori knowledge of its polarization state, and with a limited number of acquisitions. We will make our calibration code publicly available.

The dot-com bubble bursted in the year 2000 followed by a swift movement towards resource virtualization and cloud computing business model. Cloud computing emerged not as new form of computing or network technology but a mere remoulding of existing technologies to suit a new business model. Cloud robotics is understood as adaptation of cloud computing ideas for robotic applications. Current efforts in cloud robotics stress upon developing robots that utilize computing and service infrastructure of the cloud, without debating on the underlying business model. HTM5 is an OMG’s MDA based Meta-model for agent oriented development of cloud robotic systems. The trade-view of HTM5 promotes peer-to-peer trade amongst software agents. HTM5 agents represent various cloud entities and implement their business logic on cloud interactions. Trade in a peer-to-peer cloud robotic system is based on relationships and contracts amongst several agent subsets. Electronic Institutions are associations of heterogeneous intelligent agents which interact with each other following predefined norms. In Dynamic Electronic Institutions, the process of formation, reformation and dissolution of institutions is automated leading to run time adaptations in groups of agents. DEIs in agent oriented cloud robotic ecosystems bring order and group intellect. This article presents DEI implementations through HTM5 methodology.