Material remodeling and unconventional gaits facilitate locomotion of a robophysical rover over granular terrain

2020 ◽  
Vol 5 (42) ◽  
pp. eaba3499 ◽  
Author(s):  
Siddharth Shrivastava ◽  
Andras Karsai ◽  
Yasemin Ozkan Aydin ◽  
Ross Pettinger ◽  
William Bluethmann ◽  
...  
Keyword(s):  
Granular Media ◽  
Autonomous Robots ◽  
Robot Dynamics ◽  
Force Measurements ◽  
Lunar Rover ◽  
Self Organized ◽  
Wheeled Vehicle ◽  
Substrate Disturbance ◽  
Resistive Force Theory ◽  
Granular Drag

Autonomous robots and vehicles must occasionally recover from locomotion failure in loosely consolidated granular terrain. Recent mobility challenges led NASA Johnson Space Center to develop a prototype robotic lunar rover Resource Prospector 15 (RP15) capable of wheeled, legged, and crawling behavior. To systematically understand the terradynamic performance of such a device, we developed a scaled-down rover robot and studied its locomotion on slopes of dry and wet granular media. Addition of a cyclic-legged gait to the robot’s wheel spinning action changes the robot dynamics from that of a wheeled vehicle to a locomotor paddling through frictional fluid. Granular drag force measurements and modified resistive force theory facilitate modeling of such dynamics. A peculiar gait strategy that agitates and cyclically reflows grains under the robot allows it to “swim” up loosely consolidated hills. Whereas substrate disturbance typically hinders locomotion in granular media, the multimode design of RP15 and a diversity of possible gaits facilitate formation of self-organized localized frictional fluids that enable effective robust transport.

How individual interactions control aggregation patterns in gregarious arthropods

2004 ◽  
Vol 5 (2) ◽  
pp. 245-269 ◽  
Author(s):  
Jacques Gautrais ◽  
Christian Jost ◽  
Raphael Jeanson ◽  
Guy Theraulaz
Keyword(s):  
Autonomous Robots ◽  
Ecological Factors ◽  
Self Organized ◽  
Social Species ◽  
Animal Populations ◽  
Spatio Temporal ◽  
Underlying Mechanisms ◽  
The Individual ◽  
Social Components ◽  
And Control

Aggregation is one of the most widespread phenomena in animal groups and often represents a collective dynamic response to environmental conditions. In social species the underlying mechanisms mostly obey self-organized principles. This phenomenon constitutes a powerful model to decouple purely social components from ecological factors. Here we used a model of cockroach aggregation to address the problems of sensitivity of collective patterns and control of aggregation dynamics. The individual behavioural rules (as a function of neighbour density) and the emergent collective patterns were previously quantified and modelled by Jeanson et al. (2003, 2004). We first present the diverse spatio-temporal patterns of a derived model in response to parameter changes, either involving social or non-social interactions. This sensitivity analysis is then extended to evaluate the evolution of these patterns in mixed societies of sub-populations with different behavioural parameters. Simple linear or highly non-linear collective responses emerge. We discuss their potential application to control animal populations by infiltration of biomimetic autonomous robots that mimic cockroach behaviour. We suggest that detailed behavioural models are a prerequisite to do so.

scholarly journals Quasistatic kinetic avalanches and self-organized criticality in deviatorically loaded granular media

2021 ◽  
Vol 104 (2) ◽  
Author(s):  
Jordi Baró ◽  
Mehdi Pouragha ◽  
Richard Wan ◽  
Jörn Davidsen
Keyword(s):  
Granular Media ◽  
Self Organized ◽  
Self Organized Criticality

Nonlinear and Synthetic Models for Primate Societies

2000 ◽  
Author(s):  
Irenaeus J. A. te Boekhorst ◽  
Charlotte K. Hemelrijk
Keyword(s):  
Social Behavior ◽  
Real World ◽  
Autonomous Robots ◽  
Small Scale ◽  
Physical Constraints ◽  
Social Patterns ◽  
Self Organized ◽  
Spatial Configurations ◽  
Synthetic Models ◽  
Shed Light

We explore some unorthodox models for studying primate societies as self-organized and, hence, nonlinear complex systems. The incentive is that the conventional rationalist-analytic approach often leads to superfluous and contrived explanations. This is due to the habit of seeking separate explanations for each observed phenomenon, the tendency to ascribe social patterns solely to cognitive or genetic qualities of individuals, and the use of a short-sighted logic that yields naive predictions. These practices stem from the desire to produce testable predictions derived from a normative perspective, leading to a disregard of real world properties like nonlinear dynamics, the effects of numerous parallel interactions, and the importance of local spatial configurations. We illustrate how dynamical systems and individualoriented models explicitly include these features by starting from a synthetic perspective. As a result, they generate versatile, and often counterintuitive, insights into primate social behavior. The hypotheses derived in this way are parsimonious in the sense that a multitude of patterns can be traced back to one and the same minimal set of interactive dynamics. This type of model therefore leads to more integrating and comprehensive explanations than the purely function- alistic top-down approaches of cognitive science and neo-Darwinian evolutionary theory. We suggest that building autonomous robots and studying their performance might yield additional understanding of self-organized collective behavior in the real world. As mechanistic implementations of principles discovered in silica, robots form an interesting extension to individual-oriented models because they confront us with important real world conditions and physical constraints that are hard to program or would go otherwise unnoticed. In this chapter we use examples from primatology to tackle problems in the study of (small-scale) human societies. In contrast to the usual rationale, our objective is not to learn about our own kind by regarding monkeys and apes as simplified versions of humans. Instead, we argue that certain features of both human and nonhuman social behavior rest on common principles of selfstructuring and that studying these may shed light on general issues of social organization.

Experimental capabilities and limitations of a position-based control algorithm for swarm robotics

2020 ◽  
pp. 105971232093041
Author(s):  
Yating Zheng ◽  
Cristián Huepe ◽  
Zhangang Han
Keyword(s):  
Control Algorithm ◽  
Swarm Robotics ◽  
Collective Motion ◽  
Autonomous Robots ◽  
Analytical Calculation ◽  
Marginal Stability ◽  
Sensors And Actuators ◽  
Robot Swarms ◽  
Self Organized ◽  
Group Translation

Achieving efficient and reliable self-organization in groups of autonomous robots is a fundamental challenge in swarm robotics. Even simple states of collective motion, such as group translation or rotation, require nontrivial algorithms, sensors, and actuators to be achieved in real-world scenarios. We study here the capabilities and limitations in controlling experimental robot swarms of a decentralized control algorithm that only requires information on the positions of neighboring agents, and not on their headings. Using swarms of e-Puck robots, we implement this algorithm in experiments and show its ability to converge to self-organized collective translation or rotation, starting from a state with random orientations. Through a simple analytical calculation, we also unveil an essential limitation of the algorithm that produces small persistent oscillations of the aligned state, related to its marginal stability. By comparing predictions and measurements, we compute the experimental noise distributions of the linear and angular robot speeds, showing that they are well described by Gaussian functions. We then implement simulations that model this noise by adding Gaussian random variables with the experimentally measured standard deviations. These simulations are performed for multiple parameter combinations and compared to experiments, showing that they provide good predictions for the expected speed and robustness of the self-organizing dynamics.

Problem behavior in autism spectrum disorders: A paradigmatic self-organized perspective of network structures

2019 ◽  
Vol 42 ◽  
Author(s):  
Lucio Tonello ◽  
Luca Giacobbi ◽  
Alberto Pettenon ◽  
Alessandro Scuotto ◽  
Massimo Cocchi ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Problem Behaviors ◽  
Autism Spectrum ◽  
The Self ◽  
Network Structures ◽  
Self Organized ◽  
Critical Equilibrium ◽  
Self Organized Criticality ◽  
Acute Agitation ◽  
Spectrum Disorders

AbstractAutism spectrum disorder (ASD) subjects can present temporary behaviors of acute agitation and aggressiveness, named problem behaviors. They have been shown to be consistent with the self-organized criticality (SOC), a model wherein occasionally occurring “catastrophic events” are necessary in order to maintain a self-organized “critical equilibrium.” The SOC can represent the psychopathology network structures and additionally suggests that they can be considered as self-organized systems.

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