CORBYS cognitive control architecture for robotic follower

In this paper the novel generic cognitive robot control architecture CORBYS is presented. The objective of the CORBYS architecture is the integration of high-level cognitive modules to support robot functioning in dynamic environments including interacting with humans. This paper presents the preliminary integration of the CORBYS architecture to support a robotic follower. Experimental results on high-level empowerment-based trajectory planning have demonstrated the effectiveness of ROS-based communication between distributed modules developed in a multi-site research environment as typical for distributed collaborative projects such as CORBYS

ROVIS: RObust Machine VIsion for Service Robotic System FRIEND

Abstract-In this paper the vision architecture, named ROVIS, of the robotic system FRIEND is presented. The main concept of the ROVIS is the inclusion of feedback structures between different components of the vision system as well as between the vision and other modules of the robotic system to achieve high robustness against external influences of the individual system units as well as of the system as whole. The novelty of this work lies in the inclusion of feedback control at different levels of the 2D object recognition system to provide reliable inputs to the 3D object reconstruction and object manipulation modules of the robotic system FRIEND. The idea behind this approach is to change the processing parameters in a closed-loop manner so that the current image processing result at a particular processing level is driven to a desired result. The effectiveness of the ROVIS system is demonstrated through the presentation of experimental results on 3D reconstruction of different objects from FRIEND environment

Use cases for obstacle detection and track intrusion detection systems in the context of new generation of railway traffic management systems

In this paper, the concept of Obstacle Detection and Track Intrusion Detection (OD&TID) systems related to the operation of trains is introduced, along with a potential concept for such a system. The main focus of the work presented here is the identification and description of system requirements and Use Cases (UC), their detailed classification, including general UCs for mainline railway and UCs specific to freight, as well as an analysis of the UCs and of the method used. The identified UCs have been organised with respect to the mode of operation, Grade of Automation (GoA), and operating conditions. The UCs were further analysed in different UC scenarios, including the pre-conditions, system response, actions made by OD&TID and associated systems and the post use conditions of the scenarios. The priority for implementation and complexity of each UC are discussed with respect to the probability of scenario occurrence and required interfaces. This work has been carried out as part of the process to evaluate implementation constraints, risks and requirements, and the operational scenarios of the OD&TID developed within the EU-funded Shift2Rail project SMART2, which aims to design and develop a prototype OD&TID system

Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIEND

A key requirement of assistive robot vision is the robust 3D object reconstruction in complex environments for reliable autonomous object manipulation. In this paper the idea is presented of achieving high robustness of a complete robot vision system against external influences such as variable illumination by including feedback control of the object segmentation in stereo images. The approach used is to change the segmentation parameters in closed-loop so that object features extraction is driven to a desired result. Reliable feature extraction is necessary to fully exploit a neuro-fuzzy classifier which is the core of the proposed 2D object recognition method, predecessor of 3D object reconstruction. Experimental results on the rehabilitation assistive robotic system FRIEND demonstrate the effectiveness of the proposed method

An Efficient Solution for Hand Gesture Recognition from Video Sequence

The paper describes a system of hand gesture recognition by image processing for human robot interaction. The recognition and interpretation of the hand postures acquired through a video camera allow the control of the robotic arm activity: motion - translation and rotation in 3D - and tightening/releasing the clamp. A gesture dictionary was defined and heuristic algorithms for recognition were developed and tested. The system can be used for academic and industrial purposes, especially for those activities where the movements of the robotic arm were not previously scheduled, for training the robot easier than using a remote control. Besides the gesture dictionary, the novelty of the paper consists in a new technique for detecting the relative positions of the fingers in order to recognize the various hand postures, and in the achievement of a robust system for controlling robots by postures of the hands