Transitioning towards human–robot synergy in agriculture: A systems thinking perspective
Eirini Aivazidou, Naoum Tsolakis
- 发表年份
- 2022
- 引用次数
- 20
摘要
Abstract Digital transformation has unveiled new prospects for increased performance and productivity in the agricultural sector to meet rising food security needs. Continuous industrialization and unexpected disruptions (e.g., workforce mobility restrictions due to the COVID‐19 pandemic) call for the adoption of agricultural robots. However, automated solutions could be associated with societal challenges in rural areas; unemployment growth has been perceived as a major threat that jeopardizes societal welfare, potentially hindering the implementation of digital technologies. In this context, human–robot synergistic systems could act as a promising socially viable alternative. Through systems thinking, this research investigates the complex interconnections and key feedback mechanisms of automation diffusion (conventional and human–robot interactive) under the socio‐economic perceptions (drivers and barriers) of agribusinesses and rural communities. Overall, this study contributes towards eliciting the mental models that underpin the transition from agricultural robots to human–robot collaboration by transforming automation‐related societal risks into opportunities for sustainable rural development.
关键词
相关论文
Artificial intelligence: a modern approach
1995
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun
2012
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martı́n Abadi, Ashish Agarwal, Paul Barham 等 20 位作者
2016
Vision meets robotics: The KITTI dataset
Andreas Geiger, Philip Lenz, Christoph Stiller 等 4 位作者
2013