From collections of independent, mindless robots to flexible, mobile, and directional superstructures

Abstract

A swarm of simple active particles confined in a flexible scaffold is a promising system to make mobile and deformable superstructures. These soft structures can perform tasks that are difficult to carry out for monolithic robots because they can infiltrate narrow spaces, smaller than their size, and move around obstacles. To achieve such tasks, the origin of the forces the superstructures develop, how they can be guided, and the effects of external environment, especially geometry and the presence of obstacles, need to be understood. Here, we report measurements of the forces developed by such superstructures, enclosing a number of mindless active rod-like robots, as well as the forces exerted by these structures to achieve a simple function, crossing a constriction. We relate these forces to the self-organization of the individual entities. Furthermore, and based on a physical understanding of what controls the mobility of these superstructures and the role of geometry in such a process, we devise a simple strategy where the environment can be designed to bias the mobility of the superstructure, giving rise to directional motion. Simple tasks—such as pulling a load, moving through an obstacle course, or cleaning up an arena—are demonstrated. Rudimentary control of the superstructures using light is also proposed. The results are of relevance to the making of robust flexible superstructures with nontrivial space exploration properties out of a swarm of simpler and cheaper robots.

Spontaneous emergence of counterclockwise vortex motion in assemblies of pedestrians roaming within an enclosure

“…In particular, Silverberg et al’s observation that 95% of circle pits at heavy-metal concerts rotate CCW 6 may be rationalized along the same lines, considering that the circular boundary formed by passive agents around the pit also induces turning preferences. Finally, one could also envision systems composed of particles (synthetically designed 19 , 20 or natural) that exhibit some turning preference. For example, some animals are known to display handedness 21 , so it is likely that similar patterns to these reported here would be observed.…”

Social learning in swarm robotics

“…robots are stuck) or beneficial (e.g. robots physically align with one another, which can be used for collective motion [ 8 ]). local communication: robot-to-robot communication is limited in radius, whether because of technical limitations (short-range communication apparatus) or by design (constrained communication can be beneficial in dynamic environments [ 12 ]).…”

“…robots are stuck) or beneficial (e.g. robots physically align with one another, which can be used for collective motion [ 8 ]).…”

“…Work conducted at Harvard under the direction of Radhika Nagpal uses these same principles, and has shown that it is possible to program robots to self-assemble into a certain predefined shape [ 6 ] or to collectively build a 3D structure, transporting bricks to relevant locations [ 7 ]. Very recently, swarm robotics has become increasingly popular, as illustrated by the recent publication of several works on this topic in major journals [ 8 – 11 ]. In particular, the work of [ 12 ] shows that the material limitations in terms of communication distance between robots can be advantageous when the environment is dynamic and requires a fast detection of environmental changes.…”

“…Indeed, a swarm of robots is a complex system by definition, involving individuals whose interactions are difficult to model (e.g. because of the complexity of physical interactions between robots [ 8 , 13 ]). Machine learning—in particular, reinforcement learning methods inspired by natural evolution [ 14 – 16 ]—can automate the design of individual behavioural strategies, provided that it is possible to measure the performance of the swarm on the desired task (e.g.…”