Robot Tasks - Inspecting a bag for hazards
Robots can significantly impact the CBRNE Response activities by providing directed, specific, first-hand information prior to and during hot zone entry. Hot zone entry is not permitted until there is a preliminary hazard identification, responders don PPEs, decontamination facilities are established, etc. Rapid robot deployments will provide additional information and assist in directing the response. This project identified requirements for eight robotic CBRNE incident response tasks that were developed from a CTA, an IFA, and direct responder feedback.
The CTA captured unobservable cognitive processes, decisions, and judgments representing expert performance. The CTA also identified a hierarchy of HRI user levels and the CBRNE response areas most appropriate for robots. The IFA focused on the path of information through the CBRNE response system, including how the information is used and transformed. The IFA also identified important information flow bottlenecks. The identified tasks, when implemented with robots, must provide the same or similar information to that provided by human responders to the decision-making command hierarchy. The identified robotic tasks can significantly impact the response capabilities when the robots are designed and developed properly. We believe that it is necessary to formally analyze and understand how humans conduct their response tasks and apply the analysis results to robot design and development. This approach is a departure from traditional robotic development; however, the application of CTA to other domains has demonstrated dramatic improvements in the resulting technology.
Related Papers:
Humphrey, C. M., & Adams, J. A. (2009) Robotic Tasks for CBRNE Incident Response. Advanced Robotics
Related posts:
- Designing a System of User Interfaces for Controlling Robots for Emergency Incident Response
- CBRNE Event Analysis
- Emergency Response System Human-Robot Interaction User Levels
- Compass Visualizations for Human-Robotic Interaction
- Ph.D. Thesis: Information Abstraction Visualization for Human-Robot Interaction