Semiotics and Human-Robot Interaction

Keywords: Semi-autonomous robot, human-robot interaction, semiotics. Abstract: This paper describes a robot control architecture supported on a human-robot interaction model obtained directly from semiotics concepts. The architecture is composed of a set of objects defined after a semiotic sign model. Simulation experiments using unicycle robots are presented that illustrate the interactions within a team of robots equipped with skills similar to those used in human-robot interactions.

Real-Time Object Recognition using a Multi-Framed Temporal Approach

Computer Vision involves the extraction of data from images that are analyzed in order to provide information crucial to many modern technologies. Object recognition has proven to be a difficult task and programming reliable object recognition remains elusive. Image processing is computationally intensive and this issue is amplified on mobile platforms with processor restrictions. The real-time constraints demanded by robotic soccer in RoboCup competition serve as an ideal format to test programming that seeks to overcome these challenges. This paper presents a method for ball recognition by analyzing the movement of the ball. Major findings include enhanced ball discrimination by replacing the analysis of static images with absolute change in brightness in conjunction with the classification of apparent motion change

Insect inspired visual motion sensing and flying robots

International audienceFlying insects excellently master visual motion sensing techniques. They use dedicated motion processing circuits at a low energy and computational costs. Thanks to observations obtained on insect visual guidance, we developed visual motion sensors and bio-inspired autopilots dedicated to flying robots. Optic flow-based visuomotor control systems have been implemented on an increasingly large number of sighted autonomous robots. In this chapter, we present how we designed and constructed local motion sensors and how we implemented bio-inspired visual guidance scheme on-board several micro-aerial vehicles. An hyperacurate sensor in which retinal micro-scanning movements are performed via a small piezo-bender actuator was mounted onto a miniature aerial robot. The OSCAR II robot is able to track a moving target accurately by exploiting the microscan-ning movement imposed to its eye's retina. We also present two interdependent control schemes driving the eye in robot angular position and the robot's body angular position with respect to a visual target but without any knowledge of the robot's orientation in the global frame. This "steering-by-gazing" control strategy, which is implemented on this lightweight (100 g) miniature sighted aerial robot, demonstrates the effectiveness of this biomimetic visual/inertial heading control strategy

Bayesian Robot Programming

International audienceWe propose a new method to program robots based on Bayesian inference and learning. It is called BRP for Bayesian Robot Programming. The capacities of this programming method are demonstrated through a succession of increasingly complex experiments. Starting from the learning of simple reactive behaviors, we present instances of behavior combinations, sensor fusion, hierarchical behavior composition, situation recognition and temporal sequencing. This series of experiments comprises the steps in the incremental development of a complex robot program. The advantages and drawbacks of BRP are discussed along with these different experiments and summed up as a conclusion. These different robotics programs may be seen as an illustration of probabilistic programming applicable whenever one must deal with problems based on uncertain or incomplete knowledge. The scope of possible applications is obviously much broader than robotics

Emergent Ecosystem for Radical Innovation: Entrepreneurial Probing at Formula E

Entrepreneurial action is increasingly associated with innovation ecosystems because no firm alone can render the complex and interdependent services demanded in markets. Moreover, entrepreneurial firms are increasingly instigators of innovation ecosystems, rather than merely participants. However, particularly in the pursuit of radical innovation, a question arises as to how an entrepreneurial firm begins to form and shape the landscape for an emergent ecosystem. In this paper, we examine the innovation activities of Formula E, a new venture at the hub of an emerging ecosystem, aiming to transform motorsports for digital-native fans. Digital technologies are providing nearly boundless possibilities but represent uncertain opportunities in terms of their ability to engage young fans, who previously have shown little interest in motorsports. We identify probing as a way to use initiatives to provoke engagement and generate open-ended dialog and discussion. Entrepreneurial probing helps to expand the innovation landscape in search of heterogeneous need-solution pairs

Modeling direction selective visual neural network with ON and OFF pathways for extracting motion cues from cluttered background

The nature endows animals robustvision systems for extracting and recognizing differentmotion cues, detectingpredators, chasing preys/mates in dynamic and cluttered environments. Direction selective neurons (DSNs), with preference to certain orientation visual stimulus, have been found in both vertebrates and invertebrates for decades. In thispaper, with respectto recent biological research progress in motion-detecting circuitry, we propose a novel way to model DSNs for recognizing movements on four cardinal directions. It is based on an architecture of ON and OFF visual pathways underlies a theory of splitting motion signals into parallel channels, encoding brightness increments and decrements separately. To enhance the edge selectivity and speed response to moving objects, we put forth a bio-plausible spatial-temporal network structure with multiple connections of same polarity ON/OFF cells. Each pair-wised combination is filtered with dynamic delay depending on sampling distance. The proposed vision system was challenged against image streams from both synthetic and cluttered real physical scenarios. The results demonstrated three major contributions: first, the neural network fulfilled the characteristics of a postulated physiological map of conveying visual information through different neuropile layers; second, the DSNs model can extract useful directional motion cues from cluttered background robustly and timely, which hits at potential of quick implementation in visionbased micro mobile robots; moreover, it also represents better speed response compared to a state-of-the-art elementary motion detector

Embodied cognition: A field guide

The nature of cognition is being re-considered. Instead of emphasizing formal operations on abstract symbols, the new approach foregrounds the fact that cognition is, rather, a situated activity, and suggests that thinking beings ought therefore be considered first and foremost as acting beings. The essay reviews recent work in Embodied Cognition, provides a concise guide to its principles, attitudes and goals, and identifies the physical grounding project as its central research focus