20 January 2024
Photo: UHH Knowledge Technology
Our human participant study as Late-Breaking Results (LBR) and our code contribution Wrapyfi framework was accepted at the Human Robot Interaction Conference HRI ‘24 (Boulder, CO, USA) conference.
Title: Wrapyfi: A Python Wrapper for Integrating Robots, Sensors, and Applications across Multiple Middleware
Authors: Fares Abawi, Di Fu, Philipp Allgeuer, Stefan Wermter
Abstract: 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.
You can access the full paper here.