Publication

Toward Co-Working with Autonomous Agents: Rethinking Operations of Automation Systems

2025

Abstract

The growing complexity of commissioning industrial automation systems has increased the demand for simpler and more intuitive operation, often requiring domain-specific expertise. This paper explores task-oriented natural-language interaction with automation systems, a paradigm that is rapidly gaining traction particularly due to the advent of large language models (LLMs). Leveraging a multi-agent system (MAS), the authors introduce a two-phase approach for controlling an industrial gantry for pick-and-place operations. In phase one, the MAS generates an execution plan based on the user input; in phase two, the plan is executed deterministically on real-world hardware. Our preliminary results demonstrate the advantages of a chat-based human-in-the-loop (HiL) workflow for refining and validating execution plans, and they highlight the promise of natural-language interfaces for operating pick-and-place systems (Demo: Video 1, Video 2).

Official source

https://infoscience.epfl.ch/entities/publication/63886e06-e110-40fe-bd7f-c07bc70df47b

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2025

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/63886e06-e110-40fe-bd7f-c07bc70df47b

About this result

Related concepts (32)

Logistics automation

Logistics automation is the application of computer software or automated machinery to improve the efficiency of logistics operations. Typically this refers to operations within a warehouse or distribution center, with broader tasks undertaken by supply chain engineering systems and enterprise resource planning systems. Logistics automation systems can powerfully complement the facilities provided by these higher level computer systems. The focus on an individual node within a wider logistics network allows systems to be highly tailored to the requirements of that node.

Automation

Automation describes a wide range of technologies that reduce human intervention in processes, namely by predetermining decision criteria, subprocess relationships, and related actions, as well as embodying those predeterminations in machines. Automation has been achieved by various means including mechanical, hydraulic, pneumatic, electrical, electronic devices, and computers, usually in combination. Complicated systems, such as modern factories, airplanes, and ships typically use combinations of all of these techniques.

Multi-agent system

A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents. Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Intelligence may include methodic, functional, procedural approaches, algorithmic search or reinforcement learning. Despite considerable overlap, a multi-agent system is not always the same as an agent-based model (ABM).