Matthew B. Middleton
Papers
2
Total Citations
27
H-Index
2
About
Matthew B. Middleton is a robotics and autonomous systems researcher whose work focuses on integrating 3D perception with practical robotic manipulation. His most impactful contribution is a 3D perception-based robotic manipulation system for automated truck unloading, which has garnered 22 citations. This work introduced novel 3D box detection algorithms that enable robots to autonomously locate and handle cardboard boxes in challenging, unstructured environments like shipping containers and semi-trailers—a significant step toward automating logistics and supply chain operations. Middleton also explored discrete event command and control frameworks for networked military teams, addressing how autonomous systems can reliably adapt to changing mission requirements and resource constraints. His research sits at the intersection of computer vision, robotic manipulation, and systems engineering, demonstrating how perception algorithms can drive real-world automation. While his citation counts reflect a focused, early-career impact, Middleton’s work on practical, perception-driven robotics has clear implications for warehouse automation, logistics, and defense applications, making him a notable contributor to the field of autonomous manipulation systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2