From Design to Deployment: Decentralized Coordination of Heterogeneous Robotic Teams

被引:5
|
作者
St-Onge, David [1 ]
Varadharajan, Vivek Shankar [2 ]
Svogor, Ivan [2 ]
Beltrame, Giovanni [2 ]
机构
[1] Ecole Technol Super, Dept Mech Engn, INIT Robots Lab, Montreal, PQ, Canada
[2] Polytech Montreal, Dept Comp Engn & Software Engn, MIST Lab, Montreal, PQ, Canada
来源
基金
加拿大自然科学与工程研究理事会;
关键词
decentralized behaviors; swarm intelligence; heterogeneous robotic teams; over-the-air update; swarm systems; control framework; swarm programming; SWARM ROBOTICS;
D O I
10.3389/frobt.2020.00051
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Many applications benefit from the use of multiple robots, but their scalability and applicability are fundamentally limited when relying on a central control station. Getting beyond the centralized approach can increase the complexity of the embedded software, the sensitivity to the network topology, and render the deployment on physical devices tedious and error-prone. This work introduces a software-based solution to cope with these challenges on commercial hardware. We bring together our previous work on Buzz, the swarm-oriented programming language, and the many contributions of the Robotic Operating System (ROS) community into a reliable workflow, from rapid prototyping of decentralized behaviors up to robust field deployment. The Buzz programming language is a hardware independent, domain-specific (swarm-oriented), and composable language. From simulation to the field, a Buzz script can stay unmodified and almost seamlessly applicable to all units of a heterogeneous robotic team. We present the software structure of our solution, and the swarm-oriented paradigms it encompasses. While the design of a new behavior can be achieved on a lightweight simulator, we show how our security mechanisms enhance field deployment robustness. In addition, developers can update their scripts in the field using a safe software release mechanism. Integrating Buzz in ROS, adding safety mechanisms and granting field updates are core contributions essential to swarm robotics deployment: from simulation to the field. We show the applicability of our work with the implementation of two practical decentralized scenarios: a robust generic task allocation strategy and an optimized area coverage algorithm. Both behaviors are explained and tested with simulations, then experimented with heterogeneous ground-and-air robotic teams.
引用
收藏
页数:16
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