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Swarm Robotics

Swarm Robotics. Tal Saiag & Anna Itin May 2013. Motivation. One of the amazing feat of ants, is a weave of ants that join their bodies together so that they can float on water, to escape a flood.

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Swarm Robotics

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  1. Swarm Robotics Tal Saiag & Anna Itin May 2013

  2. Motivation • One of the amazing feat of ants, is a weave of ants that join their bodies together so that they can float on water, to escape a flood. • This weave carries other ants that rotate with those in formation so that they do not drown. • The ants had demonstrated a society where the sum is far more than its parts.

  3. Motivation cont. If we can recreate such ability in a group of simplistic robots, the opportunities are endless. Ants

  4. SR intro • Swarm robotics (SR) is basically large number of robots mimicking insects or animals that gather and together act as a collective such as ants or bees. • Historically, all robots in swarm robotics are identical, and preferably small. This is the homogeneous model. • No centralized control structure dictating how individual agents should behave. • Simple robots fallowing simple rules can carry out complex tasks.

  5. Physical requirements • Mechanical– keep it few, keep it simple. Also, they should be lightweight. • Electronic – similar to full size robot but just in smaller version. • Sensors– It can be surprisingly large for a small scout. It can include magnetometers, accelerometers, camera, video transmitter, microphone, vibration sensors and so forth. • Communications – There are three types of communication – intra-module (within a module), inter-modules (between n modules) and global. The communication types can be wired or wireless. • Computational System - Handling communication, sensors, and so forth. Require distributed control software and enough memory for buffered communication. Furthermore, since these robots are modular, the system must allow designers to add new modules. • Power - The on board battery must be able to support the robot for at least a few hours through various configurations of the robot.

  6. Issues • Issues in sensor fusion: communication delay and randomness from different sensor agents. • Issues in miniature robots: • Miniature robots of 10cm or less are not able to have powerful computer on board. • Miniature robot generally lacks reliable communication links. This is because these robots generally run on low power sources, which in turn can only support low power transmitters.

  7. Other issues • Deployment and Utilization: • Programming robots is a very tedious and overwhelming task for the average programmer. • The complexity, dynamical, and unstructuredness of the environment also makes it difficult to pre-determine what to code. • Large amount of knowledge is required for the reasoning.

  8. Swarm vs. Single Robot • Robotic swarms have several advantages over their more complex individual robot counterparts and are the results of using many robots instead of just one. • This is made possible by the simple design of the robot modules because they are often less expensive and easier to build. • When comparing the capabilities of a robot swarm to the capabilities of an individual robot, it is best to view the swarm as an individual entity performing complex behaviors at the macro-level.

  9. Swarm vs. Single Robot • The first improvement is an obvious one: robot swarms are able to cover more area than an individual robot. This is analogous to distributed search algorithms that are able to cover different parts of a search space at once. • Thesecond improvement over individual robots is swarm robots are fault tolerant because the swarm robotics algorithms do not require robots to depend on one another.

  10. Swarm vs. Single Robot • Another feature of robot swarms is their effectiveness scales well with the number of members. Adding more robots is all that has to be done to increase the effectiveness of a swarm. On the other hand, it is not always clear how to improve the effectiveness of an individual robot system.

  11. Examples • Homogeneous model: • Finding paths • Quadrotors • Hetrogeneousmodel: • Swarmanoid

  12. References • http://en.wikipedia.org/wiki/Swarm_robotics • http://en.wikipedia.org/wiki/Swarm_intelligence • http://ewh.ieee.org/r6/scv/ras/intro_swarm.pdf • http://coswarm.wordpress.com/2012/12/06/introduction-to-swarm-robotics/

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