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1. Human-in-the-loop: Role in Cyber Physical Agricultural Systems

   https://doi.org/10.15837/ijccc.2021.2.4166  

   Sreeram, Maitreya; Nof, Shimon Y. (April 2021, INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL)

   null (Ed.)

   With increasing automation, the ‘human’ element in industrial systems is gradually being reduced, often for the sake of standardization. Complete automation, however, might not be optimal in complex, uncertain environments due to the dynamic and unstructured nature of interactions. Leveraging human perception and cognition can prove fruitful in making automated systems robust and sustainable. “Human-in-the-loop” (HITL) systems are systems which incorporate meaningful human interactions into the workflow. Agricultural Robotic Systems (ARS), developed for the timely detection and prevention of diseases in agricultural crops, are an example of cyber-physical systems where HITL augmentation can provide improved detection capabilities and system performance. Humans can apply their domain knowledge and diagnostic skills to fill in the knowledge gaps present in agricultural robotics and make them more resilient to variability. Owing to the multi-agent nature of ARS, HUB-CI, a collaborative platform for the optimization of interactions between agents is emulated to direct workflow logic. The challenge remains in designing and integrating human roles and tasks in the automated loop. This article explains the development of a HITL simulation for ARS, by first realistically modeling human agents, and exploring two different modes by which they can be integrated into the loop: Sequential, and Shared Integration. System performance metrics such as costs, number of tasks, and classification accuracy are measured and compared for different collaboration protocols. The results show the statistically significant advantages of HUB-CI protocols over the traditional protocols for each integration, while also discussing the competitive factors of both integration modes. Strengthening human modeling and expanding the range of human activities within the loop can help improve the practicality and accuracy of the simulation in replicating a HITL-ARS. 

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2. Improving Human-Robot Collaboration Through Abstraction and Scaffolding in Planning and Programming Interfaces

   White, Nathan Thomas (April 2025, ProQuest)

   With the introduction of Industry 5.0, there is a growing focus on human-robot collaboration and the empowerment of human workers through the se of robotic technologies. Collaborative robots, or cobots, are well suited for filling the needs of industry. Cobots have a prioritization on safety and collaboration, giving them the unique ability to work in close proximity with people. This has the potential impact of increasing task productivity and efficiency while reducing ergonomic strain on human workers, as cobots can collaborate on tasks as teammates and support their human collaborators. However, effectively deploying and using cobots requires multidisciplinary knowledge spanning fields such as human factors and ergonomics, economics, and human-robot interaction. This knowledge barrier represents a growing challenge in industry, as workers lack the skills necessary to effectively leverage and realize the potential of cobots within their applications, resulting in cobots often being used non-collaboratively as a form of cheap automation. This presents several research opportunities for the creation of new cobot systems that support users in the creation of cobot interactions. The goal of this dissertation is to explore the use of abstraction and scaffolding supports within cobot systems to assist users in building human-robot collaborations. Specifically, this research (1) presents updates to the design of systems for planning and programming collaborative tasks, and (2) evaluates each system to understand how it can support user creation of cobot interactions. First, I present the CoFrame cobot programming system, a tool built on prior work, and illustrate how it supports user creation and understanding of cobot programs. Then, I present the evaluation of the system with domain experts, novices, and a real-world deployment to understand in which ways CoFrame does and does not successfully support users. I then describe the Allocobot system for allocating work and planning collaborative interactions, describing how it encodes multiple models of domain knowledge within its representation. Finally, I evaluate the Allocobot system in two real-world scenarios to understand how it produces and optimizes viable interaction plans. 

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3. Managing Collaborative Tasks within Heterogeneous Robotic Swarms using Swarm Contracts

   https://doi.org/10.1109/DAPPS55202.2022.00014  

   Mallikarachchi, Sanjaya; Dai, Can; Seneviratne, Oshani; Godage, Isuru (August 2022, IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS))

   The growing number of applications in Cyber-Physical Systems (CPS) involving different types of robots while maintaining interoperability and trust is an ongoing challenge faced by traditional centralized systems. This paper presents what is, to the best of our knowledge, the first integration of the Robotic Operating System (ROS) with the Ethereum blockchain using physical robots. We implement a specialized smart contract framework called “Swarm Contracts” that rely on blockchain technology in real-world applications for robotic agents with human interaction to perform collaborative tasks while ensuring trust by motivating the agents with incentives using a token economy with a self-governing structure. The use of open-source technologies, including robot hardware platforms such as TurtleBot3, Universal Robot arm, and ROS, enables the ability to connect a wide range of robot types to the framework we propose. Going beyond simulations, we demonstrate the robustness of the proposed system in real-world conditions with actual hardware robots. 

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4. Blockchain-Based Mechanism for Robotic Cooperation Through Incentives: Prototype Application in Warehouse Automation

   https://doi.org/10.1109/Blockchain53845.2021.00090  

   Grey, Jonathan; Seneviratne, Oshani; Godage, Isuru (December 2021, IEEE International Conference on Blockchain (Blockchain))

   The use of blockchain in cyber-physical systems, such as robotics, is an area with immense potential to address many shortcomings in robotic coordination and control. In traditional swarm robotic applications, where homogeneous robots are utilized, it is possible to replace a robot if it malfunctions, and it can be assumed that all robots are interchangeable. However, in many real-world applications spanning from search and rescue missions to future household robotic appliances, heterogeneous robots will need to work together with the other robots and human agents to achieve specific tasks. Nevertheless, no such system exists. Therefore, we propose a system that utilizes a token economy for robotic agents that makes agents responsive to token acquisition as an incentive for collaboration in achieving a given task. The economy enables the system to self-govern, even under Byzantine and adversarial settings. We further incorporate a novel subcontracting framework within a blockchain environment to allow the robotic agents to efficiently and cost-effectively perform complex jobs requiring multiple agents with various capabilities. We conducted a thorough evaluation of the system in a prototype warehouse application scenario, and the results are promising. 

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5. Authr: A Task Authoring Environment for Human-Robot Teams

   https://doi.org/10.1145/3379337.3415872  

   Schoen, Andrew; Henrichs, Curt; Strohkirch, Mathias; Mutlu, Bilge (October 2020, UIST '20: Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology)

   Collaborative robots promise to transform work across many industries and promote “human-robot teaming” as a novel paradigm. However, realizing this promise requires the understanding of how existing tasks, developed for and performed by humans, can be effectively translated into tasks that robots can singularly or human-robot teams can collaboratively perform. In the interest of developing tools that facilitate this process we present Authr, an end-to-end task authoring environment that assists engineers at manufacturing facilities in translating existing manual tasks into plans applicable for human-robot teams and simulates these plans as they would be performed by the human and robot. We evaluated Authr with two user studies, which demonstrate the usability and effectiveness of Authr as an interface and the benefits of assistive task allocation methods for designing complex tasks for human-robot teams. We discuss the implications of these findings for the design of software tools for authoring human-robot collaborative plans. 

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