Developing concepts for improved efficiency of robot work preparation

SInBot[1] is a large research project that focuses on maximizing the efficient use of mobile industrial robots during medium sized production runs. The system that will be described in this paper will focusses on the development and validation of concepts for efficient work preparation for cells of intelligent mobile robots that execute medium sized production runs. For a wide range of products, the machining tasks will be defined on an appropriate level, enabling control over the robots behavior and performance. When the system, system operator, and robots have more experience with a product the system can be controlled on a higher level (i.e. the subsystems or even robots can start allocating and executing tasks by themselves). Different test beds are used to test the diversity of aspects involved in the development of the SInBot system. The initial test bed used for this research is a combination of two Lynxmotion AL5D robots and a Samsung SUR40 multi-touch environment. In this paper, novel work preparation concepts will be described and an experiment setup is proposed to validate the model for definition and generation of tasks from a CAD file

Bayesian networks for spoken dialogue management in multimodal systems of tour-guide robots

In this paper, we propose a method based on Bayesian networks for interpretation of multimodal signals used in the spoken dialogue between a tour-guide robot and visitors in mass exhibition conditions. We report on experiments interpreting speech and laser scanner signals in the dialogue management system of the autonomous tour-guide robot RoboX, successfully deployed at the Swiss National Exhibition (Expo.02). A correct interpretation of a users (visitors) goal or intention at each dialogue state is a key issue for successful voice-enabled communication between tour-guide robots and visitors. To infer the visitors goal under the uncertainty intrinsic to these two modalities, we introduce Bayesian networks for combining noisy speech recognition with data from a laser scanner, which is independent of acoustic noise. Experiments with real data, collected during the operation of RoboX at Expo.02 demonstrate the effectiveness of the approach

Narrative Situation Assessment for Human-Robot Interaction

In this paper we address the problem of inter-preting sensory data for human-robot interaction, especially when gathered from several robots at the same time. After describing motion tracking in this context, we introduce a general framework for situation representation, and how it simplifies extraction of information suitable for complex man-machine dialogs. As a concrete implementation thereof, a narrative description of a complex scene in a public exposition is created. We regard issues of interpreting sensor data in an efficient way and discuss the effects of the number of robots on the results of the scene interpretation to show that our approach is not only scalable but also profits from a growing number of robots

Multi-Robot Human-Interation and Visitor Flow Management

In this paper we address the task of human-robot interaction in public mass exposition with several autonomous robots at a time. This implies questions regarding multi-robot control and interaction management with respect to social and commercial aspects of such an exposition. Multi-robot and interaction management is addressed with respect to visitor density and visitor flow. Human-robot interaction is modeled using the SOUL environment. Concluding we will present and discuss results from the Swiss national exhibition Expo.02 in the time from 15.05.02 to 20.10.02, with over 10000 hours of total robot operation time and more than 600000 visitors

Multimodal Interaction Management for Tour-Guide Robots Using Bayesian Networks

In this paper, we propose a Bayesian network framework for managing interactivity between a tour-guide robot and visitors in mass exhibition conditions, through robust interpretation of multi-modal signals. We report on methods and experiments interpreting speech and laser scanner signals in the spoken dialogue management system of the autonomous tour-guide robot RoboX, successfully deployed at the Swiss National Exhibition (Expo.02). A correct interpretation of a users (visitors) goal or intention at each dialogue state is a key issue for successful speech-based interaction in voice-enabled communication between robots and visitors. We introduce a Bayesian network approach for combining noisy speech recognition results with noise-independent data from a laser scanner, in order to infer the visitors goal under the uncertainty intrinsic to these two modalities. We demonstrate the effectiveness of the approach by simulation based on real observations during experiments with the tour-guide robot RoboX at Expo.02

Visitor Flow Management using Human-Robot Interaction at Expo.02

In this paper we will regard the task of operating a public mass exposition with several autonomous robots at a time. This implies questions regarding human-robot interaction, multi-robot control and interaction management. To enable human-robot interaction while guiding a tour we outline the SOUL environment. Multi-robot and interaction management are regarded with respect to visitor density and visitor flow. Concluding we will present and discuss results from the Swiss national exhibition Expo.02 in the time from 15.05.02 to 17.07.02, corresponding to 5293 hours of total robot operation time up to date and in interaction with 283319 visitors

Voice Enabled Interface for Interactive Tour Guide Robots

This paper considers design methodologies in order to develop voice-enabled interfaces for tour-guide robots to be deployed at the Robotics Exposition of the Swiss National Exhibition (Expo.02). Human-robot voice communication presents new challenges for design of fully autonomous mobile robots, in that interactivity must be robot-initiated in conversation and within a dynamic adverse environment. We approached these general problems for a voice enabled interface, tailored to limited computational resources of one on-board processor, when integrating smart speech signal acquisition, automatic speech recognition and synthesis, as well as dialogue system into the multi-modal, multi-sensor interface for the expo tour-guide robot. We also focus on particular issues that need to be addressed in voice-based interaction when planning specific tasks and research experiments for Expo.02 where tour-guide robots will interact with hundred of thousands of visitors during six months, seven days a week, ten hours per day

Design, Implementation and Exploitation of a New Fully Autonomous Tour Guide Robot

This paper presents the genesis of a tour guide robot, which has been built from the scratch based on the experience of the Autonomous Systems Lab. The production of 11 of those machines has been realized by a spin-off of the lab: BlueBotics SA. The goal was to maximize the autonomy and interactivity of the mobile platform while ensuring high robustness, security and performance. The result is an interactive moving machine named RoboX. RoboX can operate in human environments and interacts by seeing humans, talking to and looking at them, showing icons and asking them to answer its questions. The complete design of mechanics, electronics and software is presented in the first part. Then, as extraordinary test bed, the Robotics exhibition at Expo.02 (Swiss National Exhibition) permits to establish meaningful statistics over five months (from May 15 to October 20, 2002) with up to 11 robots operating at the same time

Low-level grounding in a multimodal mobile service robot conversational system using graphical models

The main task of a service robot with a voice-enabled communication interface is to engage a user in dialogue providing an access to the services it is designed for. In managing such interaction, inferring the user goal (intention) from the request for a service at each dialogue turn is the key issue. In service robot deployment conditions speech recognition limitations with noisy speech input and inexperienced users may jeopardize user goal identification. In this paper, we introduce a grounding state-based model motivated by reducing the risk of communication failure due to incorrect user goal identification. The model exploits the multiple modalities available in the service robot system to provide evidence for reaching grounding states. In order to handle the speech input as sufficiently grounded (correctly understood) by the robot, four proposed states have to be reached. Bayesian networks combining speech and non-speech modalities during user goal identification are used to estimate probability that each grounding state has been reached. These probabilities serve as a base for detecting whether the user is attending to the conversation, as well as for deciding on an alternative input modality (e.g., buttons) when the speech modality is unreliable. The Bayesian networks used in the grounding model are specially designed for modularity and computationally efficient inference. The potential of the proposed model is demonstrated comparing a conversational system for the mobile service robot RoboX employing only speech recognition for user goal identification, and a system equipped with multimodal grounding.The evaluation experiments use component and system level metrics for technical (objective) and user-based (subjective) evaluation with multimodal data collected during the conversations of the robot RoboX with users

Do we want to share our lives and bodies with robots? A 2000 people survey

For roughly two decades a new generation of robots, robotic prostheses and implantable devices is about to arise accompanied by great optimism that they will widely pervade our daily life in a near future. This paper presents the results from a survey on the question if people want to share their life and body with robots. The survey, carried out in connection with the Robotics exhibition at the Swiss National Exhibition Expo.02, counts over 2000 participants. The questionnaire covers issues on robotics in general, service and personal robots, robotic prostheses and artificial organs. While the results testify a positive attitude towards potential robotic co-workers, flat-mates or body part, they include a number of surprising answers. We find correlations in the data, discuss interpretations, speculate about the answers and cultural influences and finally conclude: Whom are we building robots for and what should they be like? To whom are we selling robots and how should we market them