Unlike conventional software, robotic software suffers from a lack of methods and processes that could systematize and facilitate development. Thus, the application of software engineering techniques is at the heart of current issues in robotics. The work presented in this paper aims to facilitate the development of robotic software and to facilitate communication between experts in the field through the use of software engineering techniques and methods. It proposes RsaML (Robotic Software Architecture Modeling Language), a Domain Specific Modeling Language (DSML) dedicated to robotics, which takes into account the different categories of robotic software architectures and makes it possible to describe the latter independently from the implementation platform. The conceptual model defining the terminology and the hierarchy of concepts used for the description and representation of robotic software architectures in RsaML are presented in this article. RsaML is defined through a meta-model which represents the abstract syntax of the language. The real-time properties of robotic software architectures are identified and included in the meta-model. The use of RsaML is illustrated through several experimental scenarios of the language: the definition of a robotic system and the description of its software architecture, the verification of the semantics of a robotic software architecture, and the modeling of a robotic system whose software architecture does not belong to the usual categories. The support tool used for implementations and experimentation is Eclipse Modeling Framework (EMF). The results of experimentation showed good working of the proposed solution and made it possible to validate the main concepts of the RsaML language.

In this paper, we present an approach to improve pointing methods and target selection on tactile human–machine interfaces. This approach defines a two-level highlighting technique (TLH) based on the direction of gaze for target selection on a touch screen. The technique uses the orientation of the user’s head to approximate the direction of his gaze and uses this information to preselect the potential targets. An experimental system with a multimodal interface has been prototyped to assess the impact of TLH on target selection on a touch screen and compare its performance with that of traditional methods (mouse and touch). We conducted an experiment to assess the effectiveness of our proposition in terms of the rate of selection errors made and time for completion of the task. We also made a subjective estimation of ease of use, suitability for selection, confidence brought by the TLH, and contribution of TLH to improving the selection of targets. Statistical results show that the proposed TLH significantly reduces the selection error rate and the time to complete tasks.