Can robots possess knowledge? Rethinking the DIK(W) pyramid through the lens of employees of an automotive factory

Hautala, Johanna

doi:10.1057/s41599-021-00893-9

Cited by 6 publications

(1 citation statement)

References 55 publications

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“…The main objective of this project is to reduce energy consumption and CO 2 emissions by automating the LB emptying process. Urban service robots lack the experience based knowledge which humans have gathered over the years while performing their jobs [17]. Similarly, MARBLE has no previous knowledge about the filling levels of the LBs.…”

Section: Introductionmentioning

confidence: 99%

Optimized Operation Management With Predicted Filling Levels of the Litter Bins for a Fleet of Autonomous Urban Service Robots

Pollak,

Gupta,

Göhlich

2024

IEEE Access

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Autonomous smart waste management services are becoming an essential component of sustainable urbanization. However, the lack of data and insights from current service-providers impedes a reliable transition from labor-intensive to autonomous services. Deploying information gathering devices make services expensive and resource-demanding. In project MARBLE (Mobile Autonomous RoBot for Litter Emptying) we are currently investigating the implementation of a fleet of service robots. In this framework, we could show that the absent filling data of litter bins (LBs) hinders the possibility of providing an energy-efficient and time-effective service. Hence, we introduce an approach where machine learningbased predictions for filling levels of LBs, derived from our extensive data gathering, are used to effectively manage the autonomous emptying process. The novel Simulated Rebalancing approach in route-planning combined with the Knapsack algorithm ensures efficient service, in comparison to the Nearest Neighbor algorithm. A promising 82% filling level prediction accuracy was achieved with the XGBoost binary classifier, as compared to the 59% baseline accuracy. Through incorporating the reliable predicted filling level data in the Simulated Rebalancing approach, a reduction of 26% in operational time and 31% in energy consumption was achieved for our simulated tests for service-event-area (SEA) James-Simon-Monbijoupark in Berlin with 49 LBs.

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Section: Introductionmentioning

confidence: 99%

Optimized Operation Management With Predicted Filling Levels of the Litter Bins for a Fleet of Autonomous Urban Service Robots

Pollak,

Gupta,

Göhlich

2024

IEEE Access

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Three-way improved neighborhood entropies based on three-level granular structures

Zhang

Zhou

Tang

et al. 2022

Int. J. Mach. Learn. & Cyber.

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Co-creating Knowledge with Robots: System, Synthesis, and Symbiosis

Hautala

Jauhiainen

2022

J Knowl Econ

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In the contemporary robotizing knowledge economy, robots take increasing responsibility for accomplishing knowledge-related tasks that so far have been in the human domain. This profoundly changes the knowledge-creation processes that are at the core of the knowledge economy. Knowledge creation is an interactive spatial process through which ideas are transformed into new and justified outcomes, such as novel knowledge and innovations. However, knowledge-creation processes have rarely been studied in the context of human–robot co-creation. In this article, we take the perspective of key actors who create the future of robotics, namely, robotics-related students and researchers. Their thoughts and actions construct the knowledge co-creation processes that emerge between humans and robots. We ask whether robots can have and create knowledge, what kind of knowledge, and what kind of spatialities connect to interactive human–robot knowledge-creation processes. The article’s empirical material consists of interviews with 34 robotics-related researchers and students at universities in Finland and Singapore as well as observations of human–robot interactions there. Robots and humans form top-down systems, interactive syntheses, and integrated symbioses in spatial knowledge co-creation processes. Most interviewees considered that robots can have knowledge. Some perceived robots as machines and passive agents with rational knowledge created in hierarchical systems. Others saw robots as active actors and learning co-workers having constructionist knowledge created in syntheses. Symbioses integrated humans and robots and allowed robots and human–robot cyborgs access to embodied knowledge.

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Can robots possess knowledge? Rethinking the DIK(W) pyramid through the lens of employees of an automotive factory

Cited by 6 publications

References 55 publications

Optimized Operation Management With Predicted Filling Levels of the Litter Bins for a Fleet of Autonomous Urban Service Robots

Optimized Operation Management With Predicted Filling Levels of the Litter Bins for a Fleet of Autonomous Urban Service Robots

Three-way improved neighborhood entropies based on three-level granular structures

Co-creating Knowledge with Robots: System, Synthesis, and Symbiosis

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