Reliable and fast sensing of the environment is a fundamental requirement for autonomous mobile robotic platforms. Unfortunately, the frame-based acquisition paradigm at the basis of main stream artificial perceptive systems is limited by low temporal dynamics and redundant data flow, leading to high computational costs. Hence, conventional sensing and relative computation are obviously incompatible with the design of high speed sensor-based reactive control for mobile applications, that pose strict limits on energy consumption and computational load. This paper introduces a fast obstacle avoidance method based on the output of an asynchronous event-based time encoded imaging sensor. The proposed method relies on an event-based Time To Contact (TTC) computation based on visual event-based motion flows. The approach is event-based in the sense that every incoming event adds to the computation process thus allowing fast avoidance responses. The method is validated indoor on a mobile robot, comparing the event-based TTC with a laser range finder TTC, showing that event-based sensing offers new perspectives for mobile robotics sensing.
Instrinsically motivated robots are machines designed to operate for long periods of time, performing tasks for which they have not been programmed for. These robots make extensive use of explorative, often unstructured actions in search for opportunities to learn and to extract information from the environment. Research in this field faces challenges that need advances not only on the algorithms but also on the experimental platforms. The iCub is a humanoid platform that was designed to support research in cognitive systems. We review in this paper the chief characteristics of the iCub robot, devoting particular attention to those aspects that makes the platform particularly suitable to the study of intrinsically motivated learning. We provide details on the software architecture, the mechanical design and the sensory system. We report examples of experiments and software modules to show how the robot can be programmed to obtain complex behaviors involving the interaction with the environment. The goal of this paper is to illustrate the potential impact of the iCub on the scientific community at large, but, in particular on the field of instrinsically motivated learning. 1 The RobotCub project was funded by the European Commission, Project IST-004370, under Strategic Objective 2.3.2.4: Cognitive Systems. 2 The iCub software and hardware are licensed under the GNU General Public License (GPL) and GNU Free Documentation License (FDL), respectively.
In recent years the robotics field has witnessed an interesting new trend. Several companies started the production of service robots whose aim is to cooperate with humans. The robots developed so far are either rather expensive or unsuitable for manipulation tasks. This article presents the result of a project which wishes to demonstrate the feasibility of an affordable humanoid robot. R1 is able to navigate, and interact with the environment (grasping and carrying objects, operating switches, opening doors etc). The robot is also equipped with a speaker, microphones and it mounts a display in the head to support interaction using natural channels like speech or (simulated) eye movements. The final cost of the robot is expected to range around that of a family car, possibly, when produced in large quantities, even significantly lower. This goal was tackled along three synergistic directions: use of polymeric materials, light-weight design and implementation of novel actuation solutions. These lines, as well as the robot with its main features, are described hereafter.
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