ACSOS 2020 (series) / Doctoral Symposium /
A Deep Domain-Specific Model Framework for Self-Reproducing Robotic Control Systems
Wed 19 Aug 2020 17:05 - 17:25 at Presentation Room C - PhD Symposium Session A Chair(s): Phyllis Nelson, Barry Porter
As robots play more critical roles in diverse and complex scenarios in the real world, monomorphic robots are limited to repeating and rather simple tasks. How to achieve a robust, flexible, and scalable multi-robot system becomes essential research. Model-driven software development (MDSD) provides a sturdy methodology for robotic programming using multilevel domain-specific languages (DSLs). These DSLs lay a solid foundation for the design, integration, and extensibility of robotic applications. In this paper, we propose a deep domain-specific model framework for the self-reproducing robotic control system to escort reliable, versatile tasks of heterogeneous robots.
Wed 19 AugDisplayed time zone: London change
Wed 19 Aug
Displayed time zone: London change
16:45 - 17:45 | PhD Symposium Session ADoctoral Symposium at Presentation Room C Chair(s): Phyllis Nelson California State Polytechnic University Pomona, Barry Porter Lancaster University | ||
16:45 20mDoctoral symposium paper | Towards realistic task and capability description in self-organizing production systems Doctoral Symposium Martin Neumayer Universität Augsburg | ||
17:05 20mDoctoral symposium paper | A Deep Domain-Specific Model Framework for Self-Reproducing Robotic Control Systems Doctoral Symposium | ||
17:25 20mDoctoral symposium paper | Interactive Knowledge-Guided Learning Doctoral Symposium Richard Nordsiek XITASO GmbH IT & Software Solutions |