Force-Based Robotic Imitation Learning: A Two-Phase Approach for Construction Assembly Tasks
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Abstract (arXiv)
The drive for efficiency and safety in construction has boosted the role of robotics and automation. However, complex tasks like welding and pipe insertion pose challenges due to their need for precise adaptive force control, which complicates robotic training. This paper proposes a two-phase system to improve robot learning, integrating human-derived force feedback. The first phase captures real-time data from operators using a robot arm linked with a virtual simulator via ROS-Sharp. In the second phase, this feedback is converted into robotic motion instructions, using a generative approach to incorporate force feedback into the learning process. This method's effectiveness is demonstrated through improved task completion times and success rates. The framework simulates realistic force-based interactions, enhancing the training data's quality for precise robotic manipulation in construction tasks.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 14 references that are in the map. First posted on arXiv 24 Jan 2025.
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6 of 14 references.
References · 6
- 2017One-Shot Visual Imitation Learning via Meta-Learningcited by 225
- 2022Rapid Locomotion via Reinforcement Learningcited by 130
- 2019Recent Advances in Imitation Learning from Observationcited by 92
- 2021Imitation Learning: Progress, Taxonomies and Challengescited by 56
- 2022Planning for Sample Efficient Imitation Learningcited by 20
- 2021A Pragmatic Look at Deep Imitation Learningcited by 9
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- 2023Learning from demonstrations: An intuitive VR environment for imitation learning of construction robots
- 2026Contact-Rich Robotic Manipulation in Construction via Zero-Shot Learning: A Diffusion Policy-Guided Adaptive Control ↗
- 2021Robotic Imitation of Human Assembly Skills Using Hybrid Trajectory and Force Learning
- 2023Cloud-Based Hierarchical Imitation Learning for Scalable Transfer of Construction Skills from Human Workers to Assisting Robots
- 2019Contact Skill Imitation Learning for Robot-Independent Assembly Programming
- 2025Sample-Efficient Robot Skill Learning for Construction Tasks: Benchmarking Hierarchical Reinforcement Learning and Vision-Language-Action VLA Model
- 2026Wrench-ACT: Enhancing Robot Policies for Contact Rich Behavior Using Direct Wrench Control
- 2021Learning Forceful Manipulation Skills from Multi-modal Human Demonstrations