We propose the S/P model (swarm/potential model) to describe the dynamics of robot swarms—that is, large groups of robots that coordinate without the use of any form of central control. The S/P model is a set of measure-valued equations that model the temporal evolution of a robot swarm and of a potential function that the swarm uses to self-coordinate. The S/P model is based on random finite s...

A new global path planning approach based on particle swarm optimization (PSO) for a mobile robot in a static environment is presented. Consider path planning as an optimization problem with constraints. The constraints are the path can not pass by the obstacles. The optimization target is the path is shortest. The obstacles in the robot’s environment are described as polygons and the vertexes ...

Using a team of small, sensor-rich robots and a larger, Parent robot, we have explored the problem of how to enable flexible, adjustable autonomy control for a multi-robot remote characterization task. To accomplish the task, the robot team must autonomously deploy into a building, efficiently search through corridors and rooms to locate a spill, and then cooperatively form a perimeter around a...

This paper proposes a learning model in which individual robots generate and acquire adaptive behaviors, that is, their own roles in an organized group without outside control. We focus upon emergent processes in which swarm robots dynamically form an organized group in coexistent subgroups. A simulation of a task to construct a truss in space using swarm robots, shows that individuals can adap...

We study how a human operator can guide a swarm of robots when transporting a large object through an environment with obstacles. The operator controls a leader robot that influences the other robots of the swarm. Follower robots push the object only if they have no line of sight of the leader. The leader represents a way point that the object should reach. By changing its position over time, t...

In this report, two systems have been developed for robot behavior acquisition using kinesthetic demonstrations. The first enables a humanoid robot to imitate constrained reaching gestures directed towards a target using a learning algorithm based on Gaussian Mixture Regression. The imitation trajectory can be reshaped in order to satisfy the constraints of the task and it can adapt to changes ...

The concept of swarm intelligence is based on the collective social behaviour of decentralized body, either natural or artificial like ant, fish, bird, bee etc. Swarm intelligence has gained very high priority among the researchers from different field like commerce, science and engineering. Multiple editions of swarm intelligence’s techniques made it suitable for optimization problems. In this...

We propose a novel method for object transport using granular convection, in which the granular material is a robot swarm consisting of small robots with minimal sensors. Granular convection is commonly observed in the “Brazil Nut Effect”. In this work, we consider the transported object to be passive, however, and not actuated like the surrounding granular material. We show that the passive ob...

Robot swarms modeled after hub-based colonies, such as ants and bees, potentially offer fault-tolerant capabilities at very favorable cost margins. However, relatively little is known about how to harness the potential of these swarms through command-and-control systems. In this paper, we study how to merge operator input with the underlying swarm behavior to maintain the fault-tolerant attribu...

Human-robot interfaces for interacting with hundreds of autonomous robots must be very different from single-robot interfaces. The central design challenge is developing techniques to maintain, program, and interact with the robots without having to handle them individually. This requires robots that can support hands-free operation, which drives many other aspects of the design. This paper pre...