Daniel N. Cassenti
Papers
9
Total Citations
54
H-Index
5
About
Daniel N. Cassenti is a leading researcher in human-robot interaction and cognitive modeling, with a focus on enhancing operator performance in military and tactical environments. His work bridges robotics, psychology, and artificial intelligence, exploring how communication styles and automation affect robot navigation and control. Cassenti’s most cited paper (15 citations) investigates the effects of communication style on robot navigation performance, using a “Wizard of Oz” paradigm to demonstrate how speech preferences can improve efficiency. He also developed the concept of a Robotics Operator Manager (ROM) for coordinating multiple robotic assets on the battlefield, modeling this role to reduce operator mental workload. His contributions to the Performance Moderated Functions Server (PMFserv) system, grounded in psychological principles, have advanced agent-based behavior modeling for military utility. With over 50 citations across his top works, Cassenti’s research has been instrumental in shaping U.S. Army Research Laboratory initiatives, particularly in Soldier-machine interaction and automation error recovery. His work offers critical insights for students and researchers interested in cognitive robotics, human factors engineering, and the future of autonomous systems in high-stakes environments.
Research Focus
Key Achievements
Top Papers
- 1The Effects of Communication Style on Robot Navigation Performance15 citations · 2009
- 2
- 3Modeling a robotics operator manager in a tactical battlefield9 citations · 2011
- 4
- 5Improvements in robot navigation through operator speech preferences5 citations · 2012
- 6Recovery from Automation Error after Robot Neglect3 citations · 2007
- 7A robotics operator manager role for military application2 citations · 2016
- 8
- 9The Effects of Communication Style on Robot Navigation Performance2 citations · 2009