Files and links (1)
Published, Version of Record (VoR)CC BY-NC V4.0, Open
Journal article
Integrating autonomy into automated research platforms
Digital discovery, v 2(5), pp 1259-1268
09 Oct 2023
Abstract
Integrating automation and autonomy into self-driving laboratories promises more efficient and reproducible experimentation while freeing scientists to focus on intellectual challenges. In the rapid advances being made towards self-driving laboratories, automation and autonomy techniques are often convoluted due to similarities between them and ambiguous language, leaving the trade-offs between them overlooked. In this perspective, we address differences between making a process occur without human intervention (automation) and providing agency and flexibility in action (autonomy). We describe the challenges of autonomy in terms of (1) orchestration, how tasks are organized and coordinated; (2) facilitation, how devices are connected and brought under automated control; and (3) scripting languages, how workflows are encoded into digital representations. Autonomous systems require advanced control architectures to handle a reactive, evolving workflow, involving control abstractions and scheduling beyond what current automation approaches provide. The specification of an autonomous system requires goal-oriented commands and context awareness, whereas automation needs exact, unambiguous instructions for reproducibility and efficiency. We contend that this contrast in design creates a need for improved standards in automation and a set of guiding principles to facilitate the development of autonomy-enabling technologies.
The strict specification required for automatization to efficiently and reproducibly act in familiar domains restricts the flexibility needed for autonomy when exploring new domains, requiring self-driving labs to balance autonomy and automation.
Metrics
Details
- Title
- Integrating autonomy into automated research platforms
- Creators
- Richard B. Canty - Massachusetts Institute of TechnologyBrent A. Koscher - Massachusetts Institute of TechnologyMatthew A. Mcdonald - Massachusetts Institute of TechnologyKlavs F. Jensen - Massachusetts Institute of Technology
- Publication Details
- Digital discovery, v 2(5), pp 1259-1268
- Publisher
- Royal Soc Chemistry
- Number of pages
- 10
- Grant note
- HR00111920025 / This work was supported by the DARPA Accelerated Molecular Discovery (AMD) program under contract HR00111920025. The authors would like to thank Dylan Walsh for intellectual discussions regarding this work. DARPA Accelerated Molecular Discovery (AMD) program; United States Department of Defense
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Chemical and Biological Engineering
- Web of Science ID
- WOS:001101655700001
- Scopus ID
- 2-s2.0-85173707070
- Other Identifier
- 991021958105904721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Chemistry, Multidisciplinary
- Computer Science, Interdisciplinary Applications