Objective:  

Make research investments in the core technologies that support the Army's autonomous mobility goals, advancing the state of the art in three critical areas:

• Developing perception technologies that allow robotic vehicles to understand their environment
• Developing intelligent control technologies enabling robotic systems to autonomously plan, execute, and monitor operational tasks undertaken in complex, tactical environments
• Developing human-machine interfaces that allow Soldiers to effectively task robotic systems and minimize operator workload

 Overview Briefing

 Research Area Technical Objectives: 

Advanced Perception for Autonomous Mobility

Develop sensors and perception algorithms to anticipate, detect, and analyze conditions that may affect unmanned ground vehicle mobility performance:

• Detect terrain conditions that may impair mobility and compromise mission effectiveness
• Anticipate conditions at long enough range to enable early decisions
• Understand the motion of other agents to safeguard the vehicle as well as other agents.

Intelligent Control Architectures and Tactical Behaviors

Develop the intelligent control architecture and algorithms to accomplish the following:

• Produce deliberate and reactive tactical behaviors to include tactical skills, individual tasks and collective tasks
• Span levels of control from sensor/servo up to small combat unit including ensemble manned-unmanned, air-ground battle teams
• Implement autonomous command, control and communications (C3) to coordinate execution of " move","look", and "shoot" tasks
• Support variable levels of operator control from fully manual to fully autonomous in realistic tactical environments
• Operate robustly in a distributed, networked environment with realistic bandwidth and quality of service assumptions

Human-Machine Interface

Investigate the interactions between human and robotic systems at varying levels of unmanned system autonomy through:

• Development and testing of an integrated Soldier Machine Interface (SMI) and family of Operator Control Units (OCUs) that is able to control heterogeneous unmanned assets and support both mounted and dismounted operations
• Development and testing of an Operational Control Language (OCL) designed to be understood by humans and machines for the Who/What/Where/When/Why of an activity
• Development of human performance models to ensure that Soldiers are comfortable using an OCU to command robotic assets and to address cognitive load issues deriving from management of multiple unmanned assets
• Examining issues of trust and dependence on imperfect automation