PROJECTPUBLICATIONSSWARM-BOTSprivate area
HARDWARESIMULATIONSCONTROL

Control





The Scenario

The Scenario
The scenario
It is a search and retrieve task which gives an example of the possible activities a swarm-bot could carry out. Moreover, this scenario shows how the s-bots can rely on self-organisation and self-assembly to achieve a given task.
  • The scenario solved by 12 real s-bots




  • Basic Behavioral Capabilities

    preview of co-ordinated motion
    Co-ordinated motion
    This concerns the design of control policies for the development of all the behavioural skills required either (i) by a single s-bot to co-ordinate its motion with respect to the movement of other s-bots located nearby (e.g., an aggregation of s-bots which negotiate a common direction of movement); or (ii) by a swarm-bot in order to achieve particular results without incurring into undesired circumstances (e.g., reaching a certain target area without crashing into obstacles, or falling into troughs, etc.).

    preview of co-ordinated motion
    Hole/obstacle avoidance
    This task has been designed for studying all-terrain collective navigation strategies. It can be considered an instance of the broader family of all-terrain navigation tasks, which generally tackle the problem of navigating in complex environments presenting obstacles, rough terrains, holes, gaps or narrow passages. Compared to other problems in the all-terrain navigation family, the hole/obstacle avoidance task represents a relatively simple instance, but it is still very interesting for the study of collective navigation behaviours for a swarm-bot.

    preview of passing over a hole
    Passing over a hole
    One of the main features a swarm-bot can exhibit is the ability to assemble in physical structures that can solve problems a single individual cannot cope with. One example of such a problem is passing over a trough that would block the navigation of a single robot. In similar situations, physical connections serve as support for those s-bots that are suspended over the gap, so that the swarm-bot as a whole can continue moving.

    preview of moving on rough terrain
    Moving on rough terrain
    All-terrain navigation requires the ability to cope with a generic rough terrain, comprising slopes and obstacles that have to be climbed. The swarm-bot has been designed intentionally for this purpose, as it presents mechanical features that allow a single individual to cope with moderately rough terrains. In this section, we show how cooperation among individual s-bots is beneficial for rough terrain navigation, whenever the individual abilities are too constraining.

    aggregation
    Aggregation
    It concerns the design of control policies for the development of all the behavioural skills required by single s-bots to get close and eventually to physically connect to each other or to an already formed swarm-bot (i.e., s-bots physically connected) by means of a gripper.


    pass
    Self-assembly
    This section addresses the problem of synthesizing controllers for groups of s-bots capable of adaptively connecting to each other, forming an assembled structure---referred to as swarm-bot and/or to an object (called the prey). In particular, we focus on controlling a group of s-bots in a fully autonomous way in order to locate, approach and connect to another sbot or the prey.

    pass
    Functional Self-assembly
    This section addresses the problem of synthesizing controllers for groups of s-bots capable of adaptively connecting to each other, forming an assembled structure---referred to as swarm-bot and/or to an object (called the prey). In particular, we focus on functional self-assembling, that is, the self-organized creation of a physically connected structure, which should be functional to the accomplishment of a particular task, by designing controllers for s-bots capable of forming a swarm-bot any time environmental contingencies prevent the single s-bot to achieve its goal.

    preview of aggregation

    Adaptive division of labour
    A swarm of robots can generally perform several different tasks concurrently. The performance of the final results depends on the number of robots that are participating in each task. If they are too few, they could not succeed. If they are too many, they could interfere with each other. This section illustrates our studies about self-organised solutions for the division of labour in a swarm-bot.



    Finding Object / Goal

    preview of finding object / goal - real

    Finding object/goal
    This concerns the design of control policies for the development of all the behavioural skills required by the s-bots in order to establish a path that links a starting area to a target area by exploiting the s-bots as beacons.

    Cooperative Transport

    preview of cooperative transport - real
    Cooperative transport
    This concerns the design of control policies for the development of all the behavioural skills required by a group of s-bots in order to approach an object and to cooperativelly transport it towards a target location (e.g., the nest).



    Swarm-bots project started
    on October 1,2001
    The project terminated
    on March 31, 2005.
    Last modified:
    Sat, 21 Aug 2010 12:46:15 -0500
    web administrator:
    swarm-bots@iridia.ulb.ac.be