Distributed Control of Robotic Swarms from Reactive High-Level Specifications

Author(s):  
Ji Chen ◽  
Ruojia Sun ◽  
Hadas Kress-Gazit
2006 ◽  
Vol 4 (4) ◽  
pp. 29 ◽  
Author(s):  
Peter Sapaty, PhD ◽  
Masanori Sugisaka, PhD ◽  
Robert Finkelstein, PhD ◽  
Jose Delgado-Frias, PhD ◽  
Nikolay Mirenkov, PhD

A novel distributed control ideology and technology will be described for management of advanced crisis relief missions. The approach is based on the installation of a universal “social” module in highly portable electronic devices, like laptops and mobile phones, which can collectively interpret a spatial scenario language, exchanging high-level program code (waves), data, and control with other modules in a parallel fashion. This technology can dynamically integrate any human and technical resources that were scattered postdisaster into an operable, distributed system capable of solving—autonomously—complex survivability, relief, and reconstruction problems.


2000 ◽  
Vol 12 (1) ◽  
pp. 29-34 ◽  
Author(s):  
Gen'ichi Yasuda ◽  

We describe the concept and implementation of modular distributed control architecture for cooperative soccer-playing robot agents. Overall complete autonomous control for robotic soccer consists of the host and several onboard control systems. Onboard control for an autonomous mobile robot with intelligent sensors and actuators is constructed on microcontrollerbased flexible, extendable architecture whose microcontrollers are dedicated to low-level control for navigation based on multiaxis and multisensor cooperation. Operations of autonomous actuators are integrated through a serial-bus communication network. Distributed implementation reduces difficulties in complex hardware and software design of the control system. We evaluated basic control executed on microcontrollers. The host conducts high-level decision-making and cooperative action planning for robot agents. The implementation of basic skills and strategies for robotic soccer is discussed.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Kai Feng ◽  
Rajyashree Sen ◽  
Ryo Minegishi ◽  
Michael Dübbert ◽  
Till Bockemühl ◽  
...  

AbstractHow do descending inputs from the brain control leg motor circuits to change how an animal walks? Conceptually, descending neurons are thought to function either as command-type neurons, in which a single type of descending neuron exerts a high-level control to elicit a coordinated change in motor output, or through a population coding mechanism, whereby a group of neurons, each with local effects, act in combination to elicit a global motor response. The Drosophila Moonwalker Descending Neurons (MDNs), which alter leg motor circuit dynamics so that the fly walks backwards, exemplify the command-type mechanism. Here, we identify several dozen MDN target neurons within the leg motor circuits, and show that two of them mediate distinct and highly-specific changes in leg muscle activity during backward walking: LBL40 neurons provide the hindleg power stroke during stance phase; LUL130 neurons lift the legs at the end of stance to initiate swing. Through these two effector neurons, MDN directly controls both the stance and swing phases of the backward stepping cycle. These findings suggest that command-type descending neurons can also operate through the distributed control of local motor circuits.


2004 ◽  
Vol 17 (1) ◽  
pp. 93-105 ◽  
Author(s):  
Wei-Min Shen ◽  
Peter Will ◽  
Aram Galstyan ◽  
Cheng-Ming Chuong

Author(s):  
Gen'ichi Yasuda

This chapter deals with the design and implementation of bio-inspired control architectures for intelligent multiple mobile robot systems. Focusing on building control systems, this chapter presents a non-centralized, behavior-based methodology for autonomous cooperative control, inspired by the adaptive and self-organizing capabilities of biological systems, which can generate robust and complex behaviors through limited local interactions. With autonomous behavior modules for discrete event distributed control, a modular, Petri net-based behavioral control software has been implemented in accordance with a hierarchical distributed hardware structure. The behavior modules with respective pre-conditions and post-conditions can be dynamically connected in response to status events from action control modules at the lower level to achieve the specified overall task. The approach involving planning, control, and reactivity can integrate high-level command input with the behavior modules through the distributed autonomous control architecture.


Author(s):  
Gen'ichi Yasuda

This chapter deals with the design and implementation of bio-inspired control architectures for intelligent multiple mobile robot systems. Focusing on building control systems, this chapter presents a non-centralized, behavior-based methodology for autonomous cooperative control, inspired by the adaptive and self-organizing capabilities of biological systems, which can generate robust and complex behaviors through limited local interactions. With autonomous behavior modules for discrete event distributed control, a modular, Petri net based behavioral control software has been implemented in accordance with a hierarchical distributed hardware structure. The behavior modules with respective pre-conditions and post-conditions can be dynamically connected in response to status events from action control modules at the lower level to achieve the specified overall task. The approach involving planning, control and reactivity can integrate high-level command input with the behavior modules through the distributed autonomous control architecture.


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