Topic
Physicomimetics
About: Physicomimetics is a research topic. Over the lifetime, 52 publications have been published within this topic receiving 1229 citations.
Papers
TL;DR: A framework that provides distributed control of large collections of mobile physical agents in sensor networks, which is founded upon solid scientific principles and provides an effective basis for self-organization, fault-tolerance, and self-repair.
Abstract: We introduce a framework, called “physicomimetics,” that provides distributed control of large collections of mobile physical agents in sensor networks. The agents sense and react to virtual forces, which are motivated by natural physics laws. Thus, physicomimetics is founded upon solid scientific principles. Furthermore, this framework provides an effective basis for self-organization, fault-tolerance, and self-repair. Three primary factors distinguish our framework from others that are related: an emphasis on minimality (e.g., cost effectiveness of large numbers of agents implies a need for expendable platforms with few sensors), ease of implementation, and run-time efficiency. Examples are shown of how this framework has been applied to construct various regular geometric lattice configurations (distributed sensing grids), as well as dynamic behavior for perimeter defense and surveillance. Analyses are provided that facilitate system understanding and predictability, including both qualitative and quantitative analyses of potential energy and a system phase transition. Physicomimetics has been implemented both in simulation and on a team of seven mobile robots. Specifics of the robotic embodiment are presented in the paper.
466 citations
2 Jul 2007
TL;DR: This paper addresses the problem of sensor management for a large network of agile sensors through a novel combination of particle filtering for nonparametric density estimation, information theory for comparing actions, and physicomimetics for computational tractability.
Abstract: This paper addresses the problem of sensor management for a large network of agile sensors. Sensor management, as defined here, is the process of dynamically retasking agile sensors in response to an evolving environment. Sensors may be agile in a variety of ways, e.g., the ability to reposition, point an antenna, choose sensing mode, or waveform. The goal of sensor management in a large network is to choose actions for individual sensors dynamically so as to maximize overall network utility. Sensor management in the multiplatform setting is a challenging problem for several reasons. First, the state space required to characterize an environment is typically of very high dimension and poorly represented by a parametric form. Second, the network must simultaneously address a number of competing goals. Third, the number of potential taskings grows exponentially with the number of sensors. Finally, in low-communication environments, decentralized methods are required. The approach we present in this paper addresses these challenges through a novel combination of particle filtering for nonparametric density estimation, information theory for comparing actions, and physicomimetics for computational tractability. The efficacy of the method is illustrated in a realistic surveillance application by simulation, where an unknown number of ground targets are detected and tracked by a network of mobile sensors.
157 citations
Journal Article•
TL;DR: An overview of the framework, called physicomimetics, for the distributed control of swarms of robots, focuses on robotic behaviors that are similar to those shown by solids, liquids, and gases.
Abstract: This paper provides an overview of our framework, called physicomimetics, for the distributed control of swarms of robots. We focus on robotic behaviors that are similar to those shown by solids, liquids, and gases. Solid formations are useful for distributed sensing tasks, while liquids are for obstacle avoidance tasks. Gases are handy for coverage tasks, such as surveillance and sweeping. Theoretical analyses are provided that allow us to reliably control these behaviors. Finally, our implementation on seven robots is summarized.
117 citations
17 Jul 2004
TL;DR: The physicomimetics framework for the distributed control of swarms of robots is described in this paper, where the authors focus on robotic behaviors similar to those shown by solids, liquids, and gases.
Abstract: This paper provides an overview of our framework, called physicomimetics, for the distributed control of swarms of robots. We focus on robotic behaviors that are similar to those shown by solids, liquids, and gases. Solid formations are useful for distributed sensing tasks, while liquids are for obstacle avoidance tasks. Gases are handy for coverage tasks, such as surveillance and sweeping. Theoretical analyses are provided that allow us to reliably control these behaviors. Finally, our implementation on seven robots is summarized.
94 citations
Book•
5 Jan 2012
TL;DR: This book introduces the term "physicomimetics" to refer to physics-based swarm approaches and consolidates over a decade of work on swarm intelligence and swarm robotics.
Abstract: This book introduces the term "physicomimetics" to refer to physics-based swarm approaches. It consolidates over a decade of work on swarm intelligence and swarm robotics.
69 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2019 | 2 |
| 2018 | 3 |
| 2017 | 1 |
| 2015 | 1 |
| 2014 | 1 |
| 2013 | 4 |