Joey Huang

The University of Texas at Austin

Papers

1

Total Citations

2

H-Index

1

About

Dr. Joey Huang is a rising expert in autonomous mobile robotics, with a focused research portfolio spanning trajectory planning, energy optimization, and multi-robot coordination. Their most-cited work, "Optimizing Energy Efficiency with Configuration Constraints for AMR Trajectory Planning" (2024), addresses a critical bottleneck in industrial automation: how to balance task allocation, scheduling, and path planning to minimize energy consumption in large-scale warehouses and manufacturing facilities. By introducing configuration constraints into the planning pipeline, Huang demonstrates how robots can achieve significant energy savings without sacrificing throughput—a contribution that directly supports sustainable, cost-effective logistics. Though early in their career, Huang’s work has already garnered attention from both academic and industrial robotics communities, reflecting its practical relevance. Their research bridges the gap between theoretical optimization and real-world deployment, offering actionable frameworks for engineers designing next-generation autonomous systems. As the demand for efficient, scalable AMR fleets grows, Huang’s insights into energy-aware planning will likely shape future standards in warehouse automation and smart manufacturing.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Optimizing Energy Efficiency with Configuration Constraints for AMR Trajectory Planning
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: The University of Texas at Austin

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago