Month: October 2017

Self-Healing and Damage Resilience for Soft Robotics: A Review

Advances in soft robotics will be crucial to the next generation of robot–human interfaces. Soft material systems embed safety at the material level, providing additional safeguards that will expedite their placement alongside humans and other biological systems. However, in order to function in unpredictable, uncontrolled environments alongside biological systems, soft robotic systems should be as robust in their ability to recover from damage as their biological counterparts. There exists a great deal of work on self-healing materials, particularly polymeric and elastomeric materials that can self-heal through a wide variety of tools and techniques. Fortunately, most emerging soft robotic systems are constructed from polymeric or elastomeric materials, so this work can be of immediate benefit to the soft robotics community. Though the field of soft robotics is still nascent as a whole, self-healing and damage resilient systems are beginning to be incorporated into three key support pillars that are enabling the future of soft robotics: actuators, structures, and sensors. This article reviews the state-of-the-art in damage resilience and self-healing materials and devices as applied to these three pillars. This review also discusses future applications for soft robots that incorporate self-healing capabilities.


Self-Healing and Damage Resilience for Soft Robotics: A Review

R. Adam Bilodeau & Rebecca K. Kramer

Front. Robot. AI, 03 October 2017 |


Phase Coexistence in Insect Swarms

Animal aggregations are visually striking, and as such are popular examples of collective behavior in the natural world. Quantitatively demonstrating the collective nature of such groups, however, remains surprisingly difficult. Inspired by thermodynamics, we applied topological data analysis to laboratory insect swarms and found evidence for emergent, material-like states. We show that the swarms consist of a core “condensed” phase surrounded by a dilute “vapor” phase. These two phases coexist in equilibrium, and maintain their distinct macroscopic properties even though individual insects pass freely between them. We further define a pressure and chemical potential to describe these phases, extending theories of active matter to aggregations of macroscopic animals and laying the groundwork for a thermodynamic description of collective animal groups.


Phase Coexistence in Insect Swarms
Michael Sinhuber and Nicholas T. Ouellette
Phys. Rev. Lett. 119, 178003 – Published 24 October 2017


Jobs: SFI Program Postdoc, Neural Network Models of Social Organizations | Santa Fe Institute

SFI seeks a program postdoc to play a key role in a project using modern information theory and numerical optimization techniques to analyze social organizations, ranging from modern firms to military organizations to complex chiefdoms to primary states. 
The starting point for the project is to identify the “organization” of a social group as the communication network(s) within that group. To begin we will adopt a group-selection perspective, assuming that the social group’s network structure is (approximately) optimal, given the information-processing limitations of the agents within the social group, and the exogenous welfare function of the overall group. We intend to leverage the computational power of neural networks to solve such problems. An expanded description of this project can be found at

This project, led by the Santa Fe Institute, is collaboration among archaeologists, economists, and computer scientists. The ideal starting date is the spring of 2018, though that is flexible. The position would last for two years, with possible extensions. 


Complex Contagions: A Decade in Review

Since the publication of ‘Complex Contagions and the Weakness of Long Ties’ in 2007, complex contagions have been studied across an enormous variety of social domains. In reviewing this decade of research, we discuss recent advancements in applied studies of complex contagions, particularly in the domains of health, innovation diffusion, social media, and politics. We also discuss how these empirical studies have spurred complementary advancements in the theoretical modeling of contagions, which concern the effects of network topology on diffusion, as well as the effects of individual-level attributes and thresholds. In synthesizing these developments, we suggest three main directions for future research. The first concerns the study of how multiple contagions interact within the same network and across networks, in what may be called an ecology of contagions. The second concerns the study of how the structure of thresholds and their behavioral consequences can vary by individual and social context. The third area concerns the roles of diversity and homophily in the dynamics of complex contagion, including both diversity of demographic profiles among local peers, and the broader notion of structural diversity within a network. Throughout this discussion, we make an effort to highlight the theoretical and empirical opportunities that lie ahead.


Complex Contagions: A Decade in Review
Douglas Guilbeault, Joshua Becker, Damon Centola


Droplets As Liquid Robots

Liquid droplets are very simple objects present in our everyday life. They are extremely important for many natural phenomena as well as for a broad variety of industrial processes. The conventional research areas in which the droplets are studied include physical chemistry, fluid mechanics, chemical engineering, materials science, and micro- and nanotechnology. Typical studies include phenomena such as condensation and droplet formation, evaporation of droplets, or wetting of surfaces. The present article reviews the recent literature that employs droplets as animated soft matter. It is argued that droplets can be considered as liquid robots possessing some characteristics of living systems, and such properties can be applied to unconventional computing through maze solving or operation in logic gates. In particular, the lifelike properties and behavior of liquid robots, namely (i) movement, (ii) self-division, and (iii) group dynamics, will be discussed.


Droplets As Liquid Robots
Jitka Čejková, Taisuke Banno, Martin M. Hanczyc and František Štěpánek