Understanding human responses to errors in a collaborative human-robot selective harvesting task

Huang, Zhuoling; Gomez, Adrian Salazar; Bird, Richie; Kalsi, Amar Singh; Jansen, Chipp; Liu, Zeyang; Miyauchi, Genki; Parsons, Simon; Sklar, Elizabeth

doi:10.31256/xp9yb4h

Cited by 3 publications

(5 citation statements)

References 15 publications

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“…Interestingly, when a field experiment was conducted to evaluate in practice the impact of the synergy on a site-specific spraying application, the proposed collaborative spraying system demonstrated a 50% reduction in the utilized sprayed pesticide [ 63 ]. Preliminary laboratory experiments in [ 82 ] investigated the opinion of experienced and non- experienced groups on errors produced by machine learning algorithms in a synergistic task.…”

Section: Resultsmentioning

confidence: 99%

Human–Robot Interaction in Agriculture: A Systematic Review

Benos

Moysiadis

Kateris

et al. 2023

Sensors

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In the pursuit of optimizing the efficiency, flexibility, and adaptability of agricultural practices, human–robot interaction (HRI) has emerged in agriculture. Enabled by the ongoing advancement in information and communication technologies, this approach aspires to overcome the challenges originating from the inherent complex agricultural environments. Τhis paper systematically reviews the scholarly literature to capture the current progress and trends in this promising field as well as identify future research directions. It can be inferred that there is a growing interest in this field, which relies on combining perspectives from several disciplines to obtain a holistic understanding. The subject of the selected papers is mainly synergistic target detection, while simulation was the main methodology. Furthermore, melons, grapes, and strawberries were the crops with the highest interest for HRI applications. Finally, collaboration and cooperation were the most preferred interaction modes, with various levels of automation being examined. On all occasions, the synergy of humans and robots demonstrated the best results in terms of system performance, physical workload of workers, and time needed to execute the performed tasks. However, despite the associated progress, there is still a long way to go towards establishing viable, functional, and safe human–robot interactive systems.

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Section: Resultsmentioning

confidence: 99%

Human–Robot Interaction in Agriculture: A Systematic Review

Benos

Moysiadis

Kateris

et al. 2023

Sensors

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“…This process was first adopted several years ago and gave a good output in time consumption [124], but it has several disadvantages reported by fruit growers that fruit and plant damage occur due to applied detachment force. However, this problem is very limited in big canopy trees and hardy fruits but has a high impact on fragile fruit and plants [125]. Another problem in bulk harvesting is that the fruit detachment is carried out without the identification of single characteristics of fruit, so most of the harvested fruit is unripe.…”

Section: End-effector Challengesmentioning

confidence: 99%

Development Challenges of Fruit-Harvesting Robotic Arms: A Critical Review

Kaleem,

Hussain,

Aqib

et al. 2023

AgriEngineering

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Promotion of research and development in advanced technology must be implemented in agriculture to increase production in the current challenging environment where the demand for manual farming is decreasing due to the unavailability of skilled labor, high cost, and shortage of labor. In the last two decades, the demand for fruit harvester technologies, i.e., mechanized harvesting, manned and unmanned aerial systems, and robotics, has increased. However, several industries are working on the development of industrial-scale production of advanced harvesting technologies at low cost, but to date, no commercial robotic arm has been developed for selective harvesting of valuable fruits and vegetables, especially within controlled strictures, i.e., greenhouse and hydroponic contexts. This research article focused on all the parameters that are responsible for the development of automated robotic arms. A broad review of the related research works from the past two decades (2000 to 2022) is discussed, including their limitations and performance. In this study, data are obtained from various sources depending on the topic and scope of the review. Some common sources of data for writing this review paper are peer-reviewed journals, book chapters, and conference proceedings from Google Scholar. The entire requirement for a fruit harvester contains a manipulator for mechanical movement, a vision system for localizing and recognizing fruit, and an end-effector for detachment purposes. Performance, in terms of harvesting time, harvesting accuracy, and detection efficiency of several developments, has been summarized in this work. It is observed that improvement in harvesting efficiency and custom design of end-effectors is the main area of interest for researchers. The harvesting efficiency of the system is increased by the implementation of optimal techniques in its vision system that can acquire low recognition error rates.

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“…In [24,25], an emulated cooperative strawberry recognition task was presented. In this work, a robot navigated the environment and relayed the images with the automatically recognized targets (together with the degrees of recognition confidence) to human test operators.…”

Section: Human-robot Cooperation (Human-robot)mentioning

confidence: 99%

“…Table 1 summarizes the basic features of the reviewed studies. [20] Harvesting Citrus Simulations Risk-averse collaboration [21] Transportation N/A Field trial Activity recognition [22] Human detection N/A Field trial Stereo vision [23] Spraying Vineyard Field trial User confirmation of machine vision [24,25] Harvesting Strawberry Simulation User confirmation of machine vision [26] Harvesting N/A Lab experiments Layered task selection [27] Spraying Canola Simulation and field trial Skills transfer interface [28] Harvesting Tea Field trial Motion coordination [29] N/A N/A Correlational study Acceptance issues [30] N/A N/A Design principles Safety issues [31] N/A N/A Design principles Safety and ergonomics issues [32] Transportation Strawberry Field trial Safety issues…”

Section: Human-robot Cooperation (Human-robot)mentioning

confidence: 99%

“…First, the time required for a single vehicle to cover a large area can be long. Second, because of the increased task duration and the workload, the energy requirements can force the UAV to cover only a small area between frequent Driving N/A Field trial EMG interface [16] Driving N/A Field trial Teleoperation platform [17][18][19] Target recognition Melon Lab experiments User confirmation of machine vision [20] Harvesting Citrus Simulations Risk-averse collaboration [21] Transportation N/A Field trial Activity recognition [22] Human detection N/A Field trial Stereo vision [23] Spraying Vineyard Field trial User confirmation of machine vision [24,25] Harvesting Strawberry Simulation User confirmation of machine vision [26] Harvesting N/A Lab experiments Layered task selection [27] Spraying Canola Simulation and field trial Skills transfer interface [28] Harvesting Tea Field trial Motion coordination [29] N/A N/A Correlational study Acceptance issues [30] N/A N/A Design principles Safety issues [31] N/A N/A Design principles Safety and ergonomics issues [32] Transportation Strawberry Field trial Safety issues…”

Section: Uav Robot Teams (Multi-uav)mentioning

confidence: 99%

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An Overview of Cooperative Robotics in Agriculture

et al. 2021

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Agricultural robotics has been a popular subject in recent years from an academic as well as a commercial point of view. This is because agricultural robotics addresses critical issues such as seasonal shortages in manual labor, e.g., during harvest, as well as the increasing concern regarding environmentally friendly practices. On one hand, several individual agricultural robots have already been developed for specific tasks (e.g., for monitoring, spraying, harvesting, transport, etc.) with varying degrees of effectiveness. On the other hand, the use of cooperative teams of agricultural robots in farming tasks is not as widespread; yet, it is an emerging trend. This paper presents a comprehensive overview of the work carried out so far in the area of cooperative agricultural robotics and identifies the state-of-the-art. This paper also outlines challenges to be addressed in fully automating agricultural production; the latter is promising for sustaining an increasingly vast human population, especially in cases of pandemics such as the recent COVID-19 pandemic.

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Understanding human responses to errors in a collaborative human-robot selective harvesting task

Cited by 3 publications

References 15 publications

Human–Robot Interaction in Agriculture: A Systematic Review

Human–Robot Interaction in Agriculture: A Systematic Review

Development Challenges of Fruit-Harvesting Robotic Arms: A Critical Review

An Overview of Cooperative Robotics in Agriculture

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