An Intelligent Tutoring System (ITS) for Future Combat Systems (FCS) Robotic Vehicle Command

1. An Intelligent Tutoring System (ITS) for Future Combat Systems (FCS) Robotic Vehicle Command I/ITSEC 2003 Presented by: Randy Jensen jensen@stottlerhenke.com Co-authors: Henry Marshall, US Army RDECOM Jeffrey Stahl, US Army RDECOM Richard Stottler, Stottler Henke

2. FCS Concept - Background • Distributed robotic vehicles and sensors are networked to control vehicles, providing • heightened situational awareness • extended sensor capabilities • reduced human risk

3. FCS – Training Challenge • New paradigm requires scenario-based practice for FCS warfighters • Formal tactical doctrine for FCS operational concept has not been developed • Desirable to minimize costs of developing and administering training – reduce requirements for human instructors and simplify scenario definition • Intelligent Tutoring Systems are effective for simulating some of the benefits of a human instructor, especially for a domain with focused, task-based exercises

4. Simulation Testbed • Embedded Combined Arms Tactical Training and Mission Rehearsal (ECATT/MR) testbed developed at RDECOM • Multi-screen control interface, on OTB simulation • Software for controlling simulated entities is the same as that used for operating robotic vehicles

5. Testbed User Interface Closeup

6. Intelligent Tutoring System (ITS) Architecture Overview • Simulation Interface provides two forms of data to Evaluation Machines: • Simulation states • Student actions • Instructional Manager sends notifications back to the student in the OCU environment, based on conclusions from the Evaluation Machines

7. Principle-Based Evaluation • Distinct evaluation mechanisms indexed to instructional principles

8. FCS ITS Instructional Principle Categories • TACTICAL DECISION MAKING • Student’s ability to interpret the tactical situation and commander’s intent, and decide what should be done • Example: Use airborne sensor assets to complement knowledge from ground-based vehicles • COMMAND FORMULATION • Student’s ability to translate tactical decisions into commands or orders that can be executed • EXECUTION • Student’s application of correct buttonology in execution

9. FCS ITSInstructional Principle Examples • TASK • Use terrain concealment • to detect enemy positions from • Unmanned Ground Vehicles (UGVs) • without being detected

10. FCS ITS Instructional Principle Examples: TACTICAL • TACTICAL: Before cresting hills in terrain, halt UGV and use mast sensors to scan for enemy

11. FCS ITS Instructional Principle Examples: COMMAND FORMULATION • COMMAND FORMULATION: When UGV movement will include successive halt and resume, control the vehicle with draggable points in the OCU

12. FCS ITS Instructional Principle Examples: EXECUTION • EXECUTION: The main HALT control halts all vehicles; the HALT control under “Assign Task” halts the current vehicle

13. Finite State Machine (FSM) Based Evaluations • What are they? • Transition networks executing in coordination with a simulation to gather data about instructionally significant events and states, and make evaluation conclusions in real time • Why use them in an ITS? • Several benefits: • Modularity – they can be used separately or in conjunction for a variety of scenarios • Instructional correspondence – individual instructional principles can be associated with independent evaluations • Integration – the FSM structure is easily integrated with free-play simulations and maps well to diagnosis of widely varied outcomes • Authoring ease – they can be represented visually, making them easy for non-programmers to create, maintain, and revise

14. Evaluation Machine Example • TACTICAL: Before cresting hills in terrain, halt UGV and use mast sensors to scan for enemy

15. Lessons Learned • Automated evaluation is suited for the domain of training the employment of robotic vehicles under the FCS concept • Streamlining domain-specific requirements (simulation integration, scoping training objectives, etc.) reduces ITS development time and cost • Preferable to avoid scenario-specific evaluation • Example: Identifying terrain where a UGV has an exposed hull. • Scenario-specific approach: Manually annotate areas on the map that represent hill crests where a UGV would be exposed • Scenario-independent approach:Use dynamic line of sight (LOS) calculations in the simulation to determine exposure

16. Future Work • Full system development with a rigorous collection of scenarios • Enhanced feedback mechanisms, potentially with controls to pause or rewind the simulation • Team training extensions • Similar architecture applies in the team setting • Scalable principle hierarchy supports reuse with scenarios involving a superset of instructional concepts • ITS capabilities proposed for Integration into the Tank and Automotive Research and Development Command (TARDEC) Crew instrumentation and Automation Testbed