Michael Rubenstein

Kilobot: A low cost scalable robot system for collective behaviors

In current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. These algorithms are generally meant to control collectives of hundreds or even thousands of robots; however, for reasons of cost, time, or complexity, they are generally validated in simulation only, or on a group of a few tens of robots. To address this issue, this paper presents Kilobot, a low-cost robot designed to make testing collective algorithms on hundreds or thousands of robots accessible to robotics researchers. To enable the possibility of large Kilobot collectives where the number of robots is an order of magnitude larger than the largest that exist today, each robot is made with only

Docking among independent and autonomous CONRO self-reconfigurable robots

14 worth of parts and takes 5 minutes to assemble. Furthermore, the robot design allows a single user to easily operate a large Kilobot collective, such as programming, powering on, and charging all robots, which would be difficult or impossible to do with many existing robotic systems.

Kilobot: A low cost robot with scalable operations designed for collective behaviors

Docking between independent groups of self-reconfigurable robotic modules enables the merger of two or more independent self-reconfigurable robots. This ability allows independent reconfigurable robots in the same environment to join together to complete a task that would otherwise not be possible with the individual robots prior to merging. The challenges for this task include: (1) coordinate and align two independent self-reconfigurable robots using the docking guidance system available only at the connectors of the docking modules; (2) overcome the inevitable errors in the alignment by a novel and coordinated movements from both docking ends; (3) ensure the secure connection at the end of docking; (4) switch configuration and let modules to discover the changes and new connections so that the two docked robots will move as a single coherent robot. We have developed methods for overcome these challenging problems and accomplished for the first time an actual docking between two independent CONRO robots each with multiple modules.

Massive uniform manipulation: Controlling large populations of simple robots with a common input signal

In current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. These algorithms are generally meant to control collectives of hundreds or even thousands of robots; however, for reasons of cost, time, or complexity, they are generally validated in simulation only, or on a group of a few tens of robots. To address this issue, this paper presents Kilobot, an open-source, low cost robot designed to make testing collective algorithms on hundreds or thousands of robots accessible to robotics researchers. To enable the possibility of large Kilobot collectives where the number of robots is an order of magnitude larger than the largest that exist today, each robot is made with only

Multimode locomotion via SuperBot robots

14 worth of parts and takes 5 min to assemble. Furthermore, the robot design allows a single user to easily operate a large Kilobot collective, such as programming, powering on, and charging all robots, which would be difficult or impossible to do with many existing robotic systems. We demonstrate the capabilities of the Kilobot as a collective robot, by using a small robot test collective to implement four popular swarm behaviors: foraging, formation control, phototaxis, and synchronization

Automatic scalable size selection for the shape of a distributed robotic collective

Roboticists, biologists, and chemists are now producing large populations of simple robots, but controlling large populations of robots with limited capabilities is difficult, due to communication and onboard-computation constraints. Direct human control of large populations seems even more challenging. In this paper we investigate control of mobile robots that move in a 2D workspace using three different system models. We focus on a model that uses broadcast control inputs specified in the global reference frame. In an obstacle-free workspace this system model is uncontrollable because it has only two controllable degrees of freedom - all robots receive the same inputs and move uniformly. We prove that adding a single obstacle can make the system controllable, for any number of robots. We provide a position control algorithm, and demonstrate through extensive testing with human subjects that many manipulation tasks can be reliably completed, even by novice users, under this system model, with performance benefits compared to the alternate models. We compare the sensing, computation, communication, time, and bandwidth costs for all three system models. Results are validated with extensive simulations and hardware experiments using over 100 robots.

SINGO: A single-end-operative and genderless connector for self-reconfiguration, self-assembly and self-healing

This paper presents a modular and reconfigurable robot for multiple locomotion modes based on reconfigurable modules. Each mode consists of characteristics for the environment type, speed, turning-ability, energy-efficiency, and recover ability from failures. The paper demonstrates this solution by the Superbot robot that combines advantages from MTRAN, CONRO and others. Experimental results, both in real robots and in simulation, have shown the validity of the approach and demonstrated the movements of forward, backward, turn, sidewinder, maneuver, and travel on batteries up to 500 meters on a flat terrain. In physics-based simulation, Superbot can perform as snake, caterpillar, insect, spider, rolling track, H-walker, etc., and move 1.0 meter/second on flat terrain with less than 6 W/module, and climb slopes of no less 40 degrees

Scalable self-assembly and self-repair in a collective of robots

A collective of robots can together complete a task that is beyond the capabilities of any of its individual robots. One property of a robotic collective that allows it to complete such a task is the shape of the collective. One method to form that shape is to form it at a size proportional to the number of robots in that collective, i.e. scalably. In our previous work, scalably forming the shape of the collective required that each robot know the total number of robots in the collective. In this work we present a method called S-DASH, which now allows a collective to scalably form a shape without knowing how many robots are in the collective. Furthermore, S-DASH will change the size of the shape to reflect the addition or removal of robots from the collective. This paper also provides demonstrations of S-DASH running on a simulated collective of robots.

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology

Flexible and reliable connection is critical for self-reconfiguration, self-assembly, or self-healing. However, most existing connection mechanisms suffer from a deficiency that a connection would seize itself if one end malfunctions or is out of service. To mitigate this limitation on self-healing, this paper presents a new SINGO connector that can establish or disengage a connection even if one end of the connection is not operational. We describe the design and the prototype of the connector and demonstrate its performance by both theoretical analysis and physical experimentations.

Rolling and Climbing by the Multifunctional SuperBot Reconfigurable Robotic System

A collective of robots can together complete a task that is beyond the capabilities of any of its individual robots. One property of a robotic collective that allows it to complete such a task is the shape of the collective.