Morphology agnostic gesture mapping for intuitive teleoperation of construction robots

Duan, Kangkang; Zou, Zhengbo

doi:10.1016/j.aei.2024.102600

Advanced Engineering Informatics

2024

DOI: 10.1016/j.aei.2024.102600

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Morphology agnostic gesture mapping for intuitive teleoperation of construction robots

Kangkang Duan,

Zhengbo Zou

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2024

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Cited by 2 publications

References 48 publications

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Training of construction robots using imitation learning and environmental rewards

Duan,

Zou,

Yang

2024

Computer aided Civil Eng

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Construction robots are challenging the paradigm of labor‐intensive construction tasks. Imitation learning (IL) offers a promising approach, enabling robots to mimic expert actions. However, obtaining high‐quality expert demonstrations is a major bottleneck in this process as teleoperated robot motions may not align with optimal kinematic behavior. In this paper, two innovations have been proposed. First, traditional control using controllers has been replaced with vision‐based hand gesture control for intuitive demonstration collection. Second, a novel method that integrates both demonstrations and simple environmental rewards is proposed to strike a balance between imitation and exploration. To achieve this goal, a two‐step training process is proposed. In the first step, an intuitive demonstration collection platform using virtual reality is utilized. Second, a learning algorithm is used to train a policy for construction tasks. Experimental results demonstrate that combining IL with environmental rewards can significantly accelerate the training, even with limited demonstration data.

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Training of construction robots using imitation learning and environmental rewards

Duan,

Zou,

Yang

2024

Computer aided Civil Eng

View full text Add to dashboard Cite

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Revolutionizing Construction through Enhanced Project Management and Sustainability with Industry 4.0 Technologies

Agha,

Saad,

Bashir

et al. 2024

joit

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With limited resources and a focus on sustainability, building industry staff face increasing pressure to innovate. This research explores best practices in construction to understand how Industry 4.0 technologies (AI, Robotics, AR/VR, Digital Twins) can transform project management. Through a bibliometric study and literature review, it identifies current technology adoption and barriers. The solution is a program for implementing these technologies to streamline operations, reduce waste, and boost participation. Key to unlocking Industry 4.0's benefits lies in addressing challenges in training, investment, and interoperability, supported by our findings.

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Morphology agnostic gesture mapping for intuitive teleoperation of construction robots

Cited by 2 publications

References 48 publications

Training of construction robots using imitation learning and environmental rewards

Training of construction robots using imitation learning and environmental rewards

Revolutionizing Construction through Enhanced Project Management and Sustainability with Industry 4.0 Technologies

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