Wrapyfi: A Python Wrapper for Integrating Robots, Sensors, and Applications across Multiple Middleware

Fuente: arXiv
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Autori principali: Abawi, Fares, Allgeuer, Philipp, Fu, Di, Wermter, Stefan
Natura: Preprint
Pubblicazione: 2023
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author Abawi, Fares
Allgeuer, Philipp
Fu, Di
Wermter, Stefan
author_facet Abawi, Fares
Allgeuer, Philipp
Fu, Di
Wermter, Stefan
contents Message oriented and robotics middleware play an important role in facilitating robot control, abstracting complex functionality, and unifying communication patterns between sensors and devices. However, using multiple middleware frameworks presents a challenge in integrating different robots within a single system. To address this challenge, we present Wrapyfi, a Python wrapper supporting multiple message oriented and robotics middleware, including ZeroMQ, YARP, ROS, and ROS 2. Wrapyfi also provides plugins for exchanging deep learning framework data, without additional encoding or preprocessing steps. Using Wrapyfi eases the development of scripts that run on multiple machines, thereby enabling cross-platform communication and workload distribution. We finally present the three communication schemes that form the cornerstone of Wrapyfi's communication model, along with examples that demonstrate their applicability.
format Preprint
id arxiv_https___arxiv_org_abs_2302_09648
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Wrapyfi: A Python Wrapper for Integrating Robots, Sensors, and Applications across Multiple Middleware
Abawi, Fares
Allgeuer, Philipp
Fu, Di
Wermter, Stefan
Robotics
Distributed, Parallel, and Cluster Computing
Message oriented and robotics middleware play an important role in facilitating robot control, abstracting complex functionality, and unifying communication patterns between sensors and devices. However, using multiple middleware frameworks presents a challenge in integrating different robots within a single system. To address this challenge, we present Wrapyfi, a Python wrapper supporting multiple message oriented and robotics middleware, including ZeroMQ, YARP, ROS, and ROS 2. Wrapyfi also provides plugins for exchanging deep learning framework data, without additional encoding or preprocessing steps. Using Wrapyfi eases the development of scripts that run on multiple machines, thereby enabling cross-platform communication and workload distribution. We finally present the three communication schemes that form the cornerstone of Wrapyfi's communication model, along with examples that demonstrate their applicability.
title Wrapyfi: A Python Wrapper for Integrating Robots, Sensors, and Applications across Multiple Middleware
topic Robotics
Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2302.09648