4 papers
Sample-Efficient Robot Skill Learning for Construction Tasks: Benchmarking Hierarchical Reinforcement Learning and Vision-Language-Action VLA Model
Zhaofeng Hu, Hongrui Yu, Vaidhyanathan Chandramouli +1
This study evaluates two leading approaches for teaching construction robots new skills to understand their applicability for construction automation: a Vision-Language-Action (VLA…
Phase-Adaptive LLM Framework with Multi-Stage Validation for Construction Robot Task Allocation: A Systematic Benchmark Against Traditional Optimization Algorithms
Shyam prasad reddy Kaitha, Hongrui Yu
Multi-robot task allocation in construction automation has traditionally relied on optimization methods such as Dynamic Programming and Reinforcement Learning. This research introd…
Generalizable Skill Learning for Construction Robots with Crowdsourced Natural Language Instructions, Composable Skills Standardization, and Large Language Model
Hongrui Yu, Vineet R. Kamat, Carol C. Menassa
The quasi-repetitive nature of construction work and the resulting lack of generalizability in programming construction robots presents persistent challenges to the broad adoption…
Enabling Building Information Model-Driven Human-Robot Collaborative Construction Workflows with Closed-Loop Digital Twins
Xi Wang, Hongrui Yu, Wes McGee +2
The introduction of assistive construction robots can significantly alleviate physical demands on construction workers while enhancing both the productivity and safety of construct…