Ola—what goes up must fall down: emergent Mexican wave behavior

We made a LEGO Mindstorms robot soccer model using a distributed behaviour-based system, which was showcased at RoboCup98 during the soccer World Cup in France 1998. To put the robot soccer game into an appropriate context, we also constructed a stadium out of LEGO pieces, including stadium lights, rolling commercials, moving cameras projecting images onto big screens, a scoreboard and approximately 1500 small LEGO spectators who did the “Mexican wave” as seen in soccer stadiums. These devices were controlled using the LEGO Dacta Control Lab system and the LEGO CodePilot system that allow programming motor reactions which can be based on sensor inputs. The wave of the LEGO spectators was made using the principle ofemergent behaviour. There was no central control of the wave, but it emerges from the interaction between small units of spectators with a local feedback control. This work was presented, in part, at the Foirth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999     

Using Virtual Pheromones and Cameras for Dispersing a Team of Multiple Miniature Robots

To safely and efficiently guide personnel of search and rescue operations in disaster areas, swift gathering of relevant information such as the locations of victims, must occur. Using the concept of ‘repellent virtual pheromones’ inspired by insect colony coordination behaviors, miniature robots can be quickly dispersed to survey a disaster site. Assisted by visual servoing, dispersion of the miniature robots can quickly cover an area. An external observer such as another robot or an overhead camera is brought into the control loop to provide each miniature robot estimations of the positions of all of the other near-by robots in the robotic team. These miniature robots can then move away from the other near-by robots on the team, resulting in the robot collective becoming swiftly distributed through the local area. The technique has been simulated with differing pheromone persistence levels and implemented using the miniature Scout robots, developed by the Center for Distributed Robotics at the University of Minnesota, which are well-suited to surveillance and reconnaissance missions.     

RoboMusic: a behavior-based approach

Based on principles from modern artificial intelligence and robotics, we developed the RoboMusic concept. In RoboMusic, we use a number of robotic devices as instruments, and the tunes are composed as a behavior-based system. The music artist composes a baseline behavior for the robotic instruments, and composes the behavioral response to interactions by human musicians. The music artist is transformed from a composer of static music tunes to a developer of robot behavior: behavior that is expressed by the robotic system as music pieces. Music compositions are transformed to become robotic behavior as in a behavior-based system. A RoboMusic concert is performed with robotic instruments, and changes the concept of live concerts by inviting the audience to interact with the band’s instruments themselves and thereby guide the live performance of the music themselves. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Sharing a life with Harvey: Exploring the acceptance of and relationship-building with a social robot

Social robots will become ubiquitous in our everyday environments. These robots could potentially extend life expectancy, and improve the health and quality of life of an aging population. A long-term explorative study has been conducted by installing a social robot for health promotion in elderly people’s own homes. Content analysis of interviews provided an in-depth understanding of the factors that influence the acceptance of and relationship-building with social robots in domestic environments. The permanent presence of a robot in users’ own homes yields the vital challenges social robots encounter to be successfully accepted by their users. These vital acceptance challenges are unlikely to be revealed in one-day laboratory human-robot interaction studies or even in multiple observations of short interactions between humans and robots.     

Ubiquitous robotics: Recent challenges and future trends

Ambient intelligence, ubiquitous and networked robots, and cloud robotics are new research hot topics that have started to gain popularity among the robotics community. They enable robots to acquire richer functionalities and open the way for the composition of a variety of robotic services with three functions: semantic perception, reasoning and actuation. Ubiquitous robots (ubirobots) overcome the limitations of stand-alone robots by integrating them with web services and ambient intelligence technologies. The overlap that exists now between ubirobots and ambient intelligence makes their integration worthwhile. It targets to create a hybrid physical–digital space rich with a myriad of proactive intelligent services that enhance the quality and the way of our living and working. Furthermore, the emergence of cloud computing initiates the massive use of a new generation of ubirobots that enrich their cognitive capabilities and share their knowledge by connecting themselves to cloud infrastructures. The future of ubirobots will certainly be open to an unlimited space of applications such as physical and virtual companions assisting people in their daily living, ubirobots that are able to co-work alongside people and cooperate with them in the same environment, and physical and virtual autonomic guards that are able to protect people, monitor their security and safety, and rescue them in indoor and outdoor spaces. This paper introduces the recent challenges and future trends on these topics.     

Qualitative Navigation for Autonomous Wheelchair Robots in Indoor Environments

This article describes a novel qualitative navigation method for autonomous wheelchair robots in typical home environments. The method accepts as input a line diagram of the robot environment and converts it into an enhanced grid in which qualitative representations of variations in sensor behavior between adjacent regions in space are stored. An off-line planner uses these representations to store at each grid cell appropriate motion commands that will ideally move the wheelchair in and out of each room in a typical home environment. An online controller accepts as input this enhanced grid along with a starting and goal position for the robot. It then compares the actual behavior of the sensors with the one stored in the grid. The results of this comparison are used to estimate the current position of the robot, to retrieve the planner instructions and to combine these instructrions with appropriate risk avoidance behaviors during navigation. This method has been tested both in simulation and as one of the subsystems on a prototype for an autonomous wheelchair robot. Results from both trials are provided.     

Simulation and control of distributed robot search teams

This article describes the simulation of distributed autonomous robots for search and rescue operations. The simulation system is utilized to perform experiments with various control strategies for the robot team and team organizations, evaluating the comparative performance of the strategies and organizations. The objective of the robot team is to, once deployed in an environment (floor-plan) with multiple rooms, cover as many rooms as possible. The simulated robots are capable of navigation through the environment, and can communicate using simple messages. The simulator maintains the world, provides each robot with sensory information, and carries out the actions of the robots. The simulator keeps track of the rooms visited by robots and the elapsed time, in order to evaluate the performance of the robot teams. The robot teams are composed of homogenous robots, i.e., identical control strategies are used to generate the behavior of each robot in the team. The ability to deploy autonomous robots, as opposed to humans, in hazardous search and rescue missions could provide immeasurable benefits.     

Olfactory coordinated area coverage

This paper proposes an olfaction based methodology to automatically cover an unknown area enabling the decoupled cooperation of a group of floor cleaning mobile robots. This method is based on the utilisation of low cost chemical sensors in cleaning mobile robots, in order to differentiate clean from dirty areas. The experimental results show that the use of olfactory capabilities allows to efficiently cover and clean a certain area, and demonstrate the possibility of coordinating several mobile robots without the need of expensive sensing capabilities, map building or complex algorithms for task scheduling.     

Applied ontologies and standards for service robots

Service robotics is an emerging application area for human-centered technologies. The rise of household and personal assistance robots forecasts a human–robot collaborative society. One of the robotics community’s major task is to streamline development trends, work on the harmonization of taxonomies and ontologies, along with the standardization of terms, interfaces and technologies. It is important to keep the scientific progress and public understanding synchronous, through efficient outreach and education. These efforts support the collaboration among research groups, and lead to widely accepted standards, beneficial for both manufacturers and users. This article describes the necessity of developing robotics ontologies and standards focusing on the past and current research efforts. In addition, the paper proposes a roadmap for service robotics ontology development. The IEEE Robotics & Automation Society is sponsoring the working group Ontologies for Robotics and Automation. The efforts of the Working group are presented here, aiming to connect the cutting edge technology with the users of these services—the general public.     

Biologically inspired decision-making in the robot platform MAMoRo

An important step in coming near to building machines with artificial intelligence is by studying and understanding how the human brain works, then applying this knowledge to build machines that “think” using the same concept. MAMoRo (modular autonomous mobile robot) is a general-purpose robot platform targeted at teaching and research in the academia. It consists of three modules: power and motion module, control module, and intelligence module. The decision unit of MAMoRo is distributed into two modules: the control module, which is equipped with a low-cost microcontroller, and handles low-level hardware functions, and the intelligence module, which is equipped with a field-programmable gate array (FPGA) and handles high-level functions. This model of distribution was inspired by the anatomy of the human brain and brings with it many advantages. To prove the concept, MAMoRo was tested with a practical application. This work was presented in part at the First European Workshop on Artificial Life and Robotics, Vienna, Austria, July 12–13, 2007     

Integrated architecture for industrial robot programming and control

As robot control systems are traditionally closed, it is difficult to add supplementary intelligence. Accordingly, as based on a new notion of user views, a layered system architecture is proposed. Bearing in mind such industrial demands as computing efficiency and simple factory-floor operation, the control layers are parameterized by means of functional operators consisting of pieces of compiled code that can be passed as parameters between the layers. The required interplay between application-specific programs and built-in motion control is thereby efficiently accomplished. The results from experimental evaluation and several case studies suggest the architecture to be very useful also in an industrial context.     

Active Markov localization for mobile robots

Localization is the problem of determining the position of a mobile robot from sensor data. Most existing localization approaches are passive, i.e., they do not exploit the opportunity to control the robot's effectors during localization. This paper proposes an active localization approach. The approach is based on Markov localization and provides rational criteria for (1) setting the robot's motion direction (exploration), and (2) determining the pointing direction of the sensors so as to most efficiently localize the robot. Furthermore, it is able to deal with noisy sensors and approximative world models. The appropriateness of our approach is demonstrated empirically using a mobile robot in a structured office environment.