Wallace Lawson

United States Naval Research Laboratory

Papers

14

Total Citations

148

H-Index

6

About

Wallace Lawson’s research lies at the intersection of robotics, computer vision, and human-robot interaction, with a strong focus on autonomous security and collaborative systems. His most cited work, "Finding Anomalies with Generative Adversarial Networks for a Patrolbot" (45 citations), introduces a GAN-based anomaly detection system for patrol robots, enabling autonomous identification of suspicious objects by comparing live views with learned models of normality. This foundational contribution extends to mobile platforms for detecting anomalous objects (12 citations), where deep neural network features are clustered to build environmental dictionaries. Lawson is also a pioneer in soft-biometric person identification, with two papers (25 and 23 citations) demonstrating how robots can recognize individuals using diverse features for long-term social interaction. His work on human-robot firefighting teams (10 citations) showcases cooperative strategies combining speech and gesture, while his research on touch recognition for collaborative firefighting (6 citations) addresses communication in chaotic, visually degraded environments like ship fires. Additional contributions include multimodal identification using Markov logic networks and learning speaker recognition models through interaction. With over 130 total citations, Lawson’s work advances practical, deployable robotic systems for security, emergency response, and social interaction.

Research Focus

Key Achievements

6
H-Index
14
Papers
148
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Finding Anomalies with Generative Adversarial Networks for a Patrolbot
45 citations · 2017
📈 Most Prolific Year: 2017 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: United States Naval Research Laboratory

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago