Antonio D'Angelo

Cooperation Issues and Distributed Sensing for Multirobot Systems

This paper considers the properties a multirobot system should exhibit to perform an assigned task cooperatively. Our experiments regard specifically the domain of RoboCup middle-size league (MSL) competitions. But the illustrated techniques can be usefully applied also to other service robotics fields like, for example, videosurveillance. Two issues are addressed in the paper. The former refers to the problem of dynamic role assignment in a team of robots. The latter concerns the problem of sharing the sensory information to cooperatively track moving objects. Both these problems have been extensively investigated over the past years by the MSL robot teams. In our paper, each individual robot has been designed to become reactively aware of the environment configuration. In addition, a dynamic role assignment policy among teammates is activated, based on the knowledge about the best behavior that the team is able to acquire through the shared sensorial information. We present the successful performance of the Artisti Veneti robot team at the MSL Challenge competitions of RoboCup-2003 to show the effectiveness of our proposed hybrid architecture, as well as some tests run in laboratory to validate the omnidirectional distributed vision system which allows us to share the information gathered by the omnidirectional cameras of our robots

Emergent behaviors of a robot team performing cooperative tasks

We investigate the problem of how to make a multi-robot system performing a cooperative task by inducing a set of emergent actions. We model the environment dynamics by considering some parameters that express the ability of each robot to perform its task. Thus, the members of a group of robots become aware of their ability to realize some tasks by simply computing some quality function Q of the configuration pattern of the environment. A role assignment schema allows roles to be swapped among the robots of the group in order to select the best behaviors able to perform the task cooperatively. We illustrate this approach by showing how two soccer robots were able to exchange a ball, during a real game, by combining the use of efficient collision avoidance algorithms with role swapping triggered by the value of the above quality function Q.

Intelligent multirobot systems performing cooperative tasks

We discuss how to plan the actions of a multirobot system acting in the real world by using task constraints for implicit coordination. Classifying and modelling task constraints is shown to be a very powerful mechanism for giving each robot an extended capability of coordinating itself with the other robots of the whole system. Thus, we investigate the problem of performing collective tasks with emphasis on the use of task constraints to get intelligent coordination among the individual members of the robot group. We have also introduced a set of macroscopic parameters that allow us to evaluate the evolution of the whole system. They depend on both the global task, and the environment dynamics, allowing the robots to implicitly communicate their intention to be involved in complex actions. Other group members become aware of their task simply by recognizing configuration patterns of the environment. We illustrate some examples of such a coordination taken from the scenario of both service robotics and of simulated robot games.

Making Collective Behaviours to work through Implicit Communication

The aim of this paper is to investigate how stigmergic information allow each individual of a group of autonomous robots to take advantages from other individual behaviors. The proposed analysis is based on the roboticle model where sensor data and effector commands are treated as energy exchange between the robot and its environment, eventually populated by other robots. Without explicit communication, the collective behavior of a group of teammates can be forced only if the robot designer makes each robot to become aware of distinguishing configuration patterns in the environment. Usually, the job is accomplished both by evaluating descriptive conditions as macroparameters and an appropriate dynamic role assignment among teammates. Since observed individual behaviors can affect the normal course of operations for each robot propagating to other teammates, we want to address some issues on how a collective behavior is fired and maintained.

Using a Chemical Metaphor to Implement Autonomous Systems

The aim of this paper is to outline a planning system architecture which allows robots to exhibit varying degrees of autonomous behaviour. While several systems have been developed to cope with specific classes of robot tasks, a litte effort has been made towards the autonomy itself. Looking at the behaviour of animals from the ethological point of view we can suppose that even robots need to exibit a wide variety of specific behaviours. Starting from Brooks and Rosenscheins approach we can think of an autonomous system as a vertical composition of its basic behaviours, or instincts, to produce the overall emergent activity. The key point, however, is how to really obtain it considering that robot actions require to be planned in some way to complete thenmission. In this paper we propose an analternative way to design and build an autonomous system introducing the metaphor of a chemical machine. We th ink of the whole system as a set of behaviours, each implementing a specific response to incoming environmental stimuli, equipped with appropriate receptors which can be inhibited if a behaviour is not currently requested. Such an inhibitor schema is directly driven by the system itself using sensor data and the knowledge it has about its state. The advantage of this robot design lies in its ability to make explicit the adaptive capabilities of the system during its implementation.

A Reactive Architecture for RoboCup Competition

We illustrate PaSo-Team (The University of Padua Simulated Robot Soccer Team), a Multi-Agent System able to play soccer game for participating to the Simulator League of RoboCup competition. PaSo-Team looks like a partially reactive system built upon a number of specialized behaviors, just designed for a soccer play game and generating actions accordingly with environmental changes. A general description of the architecture and a guideline of main ideas is presented in the paper, whereas a more detailed description of actual implementation is given in the appendix.

Cooperative control through objective achievement

Cooperative control is a key issue for multirobot systems in many practical applications. In this paper, we address the problem of coordinating a set of mobile robots in the RoboCup soccer middle-size league. We show how the coordination problem that we face can be cast as a specific coalition formation problem, and we propose a distributed algorithm to efficiently solve it. Our approach is based on the distributed computation of a measure of satisfaction (called Agent Satisfaction) that each agent computes for each task. We detail how each agent computes the Agent Satisfaction by acquiring sensor perceptions through an omnidirectional vision system, extracting aggregated information from the acquired perception, and integrating such information with that communicated by the teammates. We empirically validate our approach in a simulated scenario and within RoboCup competitions. The experiments in the simulated scenario allow us to analyse the behaviour of the algorithm in different situations, while the use of the algorithm in real competitions validates the applicability of our approach to robotic platforms involved in a dynamic and complex scenario.

Issues on Autonomous Agents from a Roboticle Perspective

Autonomous robots, like living systems, must be adaptive in nature if we want them to preserve their integrity while completing their mission. The challenge to survive in their environment is better accomplished if they are open systems, interacting with the environment by exchanging matter, energy, information, and so on. The roboticle framework, presented here forth, is an attempt to model how the autonomous robot control unit works. It borrows from living systems the idea that sensing and acting on the environment can be recognized as a mechanism exchanging energy with the environment in order to maintain an highly organized internal control structure to resist to external applied perturbations. The necessary energy balancing is provided by an autopoietic loop which is fed by the energy entering the robot through its sensor devices and it is dissipated by its effectors for properly acting in the environment. The autopoietic loop is also responsible of the adaptive properties of the robot.

Horn: An inference engine prototype to implement intelligent systems

The main objective of this paper is to present a prototype implementation of the kernel of an inference engine whose behaviour could be driven both by the search space strategy stored in the knowledge base and the base beliefs on which the inference engine is applied. To this aim, a modal logic language is introduced as a deductive model of knowledge and belief and some properties are derived to be used as an abstract view of the inference engine.