Collaborative Autonomy for UV Teams Paper

Collaborative Autonomy for Manned/Unmanned Teams

Steve Jameson and Jerry Franke Robert Szczerba and Sandy Stockdale
Lockheed Martin - Advanced Technology Lockheed Martin Systems Integration – Owego

Laboratories [email protected]
[email protected]

Abstract
UAVs offer tantalizing capabilities to the warfighter, such as tireless observation, quick recognition, and rapid reaction to
today’s changing battlespace. These trends are important because they aid Warfighter in their duties. Today, unmanned
systems exist that extend the vision and the reach of the Warfighter. However, they spend so much time managing these
assets that they lose effectiveness as a Warfighter. This is a particular problem if the warfighter’s role is one demanding
continuous sensory and mental workload, such as the Co-Pilot/Gunner (CPG) of an Apache Longbow attack helicopter.
Autonomy, the ability of vehicles to conduct most of their operation without human supervision, can help relieve the burden
of providing continuous oversight of the UAV’s operation. This moves the Warfighter’s role from control to command,
enabling them to perform their duties more effectively and successfully. Collaboration, the ability of teams of vehicles to
coordinate their activities without human oversight, moves unmanned systems to the level of a true force multiplier, giving
a single human warfighter the power of multiple coordinated, intelligent platforms.

Introduction1 Figure 1. Unmanned Vehicle Teams on the digital
Lockheed Martin has developed a general architecture for battlefield can act as a force multiplier if they
Collaborative Autonomy that provides both the Autonomy have the autonomy and collaboration capabilities
and the Collaboration necessary to achieve this force necessary to operate in teams without extensive
multiplication. This architecture provides the capability for human supervision.
individual unmanned vehicles to operate with unparalleled
degrees of intelligence and autonomy, and for groups of and the unmanned vehicle – the Manned/Unmanned Team –
unmanned vehicles to operate together effectively as a to perform tasks more effectively or more safely than a
team, providing greater effectiveness than an equal number human warfighter can alone. This trend is certain to
of vehicles operating independently. Collaborative continue, since UVs have proven their effectiveness
Autonomy allows the human warfighter to command the repeatedly in conflicts from Bosnia and Kosovo to
unmanned vehicles as an active member of a warfighting Afghanistan and Iraq. For a variety of reasons, it is not
team, rather than as a detached controller (Figure 1). likely that we will see unmanned vehicles operating with
full autonomy in most military applications in the
Central to the architecture are state-of-the-art software foreseeable future, and so the paradigm of
components for Mission Planning, Collaboration, Manned/Unmanned Teaming will continue to be the
Contingency Management, Situational Awareness, dominant approach to the deployment of UVs in military
Communications Management, Resource Meta-Controller, applications.
and Vehicle Management. Lockheed Martin is currently
employing and expanding this architecture to turn state-of- One of the domains of particular interest is the teaming of
the-art unmanned vehicles into transformational Unmanned Air Vehicles (UAVs) with human pilots in a
warfighting teams. scout or attack helicopter such as an Apache Longbow. The
US Army, US Navy, and DARPA have pursued the
Background development of manned/unmanned teaming with human
The U.S. Military relies heavily on the use of unmanned
vehicles (UVs) for a variety of tasks, including surveillance
and reconnaissance, explosive ordnance disposal, and to an
increasing degree for strike against terrorist and other
targets. In all cases, the unmanned vehicle operates under
the direct supervision or control of a human warfighter. The
goal of the unmanned vehicles is to provide a force
multiplier for the human warfighter that enables the human

1 Presented at the American Helicopter Society 61th Annual Forum,
Grapevine, TX, June 1-3, 2005. Copyright © 2005 by the American
Helicopter Society International, Inc. All Rights Reserved.
Distribution Statement A: Approved for Public Release, Distribution
Unlimited.

helicopter pilots on several programs, including the Army’s already has a demanding workload. This collaborative
Airborne Manned/Unmanned System Technology autonomy approach enables an unmanned vehicle team to
Demonstration (AMUST-D) and Hunter Standoff Killer be truly transformational by enabling the following five
Team (HSKT) ACTD, the Navy’s Intelligent Autonomy critical attributes (Figure 2):
Future Naval Capability (IA-FNC) program, and the
DARPA/Army Unmanned Combat Armed Rotorcraft • Intelligent – Autonomous Mission Planning and
(UCAR) program, with Lockheed Martin as a participant. Execution rapidly finds and implements the best
To meet the demanding requirements of achieving a robust solution to complex tactical problems, ensuring
force multiplier capability while limiting human workload mission success on a dynamic battlefield.
demands, Lockheed Martin has developed an architecture
and a set of technologies for Collaborative Autonomy which • Collaborative – Collaboration and Teaming
provides: capabilities produce a lethal warfighting team that
shares information, responsibilities, and tasks. It
• A high degree of autonomy for each individual interacts with human warfighters and other systems as
vehicle, enabling robust and sophisticated capabilities a team and not as separate individuals.
with limited human intervention
• Aware – Comprehensive, shared, and predictive
• Collaborative team operations, enabling multiple Situational Awareness overcomes the “fog of war” to
vehicles to operate as a team with the human enable precision engagements with precision
warfighter; allowing a single human to command information.
multiple vehicles with no more workload than a single
vehicle. • Responsive – Holistic Contingency Management
ensures survival and mission effectiveness of UVs
In this paper, we provide an overview of the Collaborative teams in the face of the unexpected, including a
Autonomy approach, describe the details of the “reflexive response” capability that allows intelligent
Collaborative Autonomy components, and describe a “short-circuiting” of higher level planning functionality
prototype implementation of the Collaborative Autonomy for rapidly changing battlefield conditions.
architecture as a Manned/Unmanned teaming
demonstration. • Agile – Tactile Maneuvering exploits terrain and
avoids obstacles, enabling the unmanned vehicle to
Approach to Collaborative Autonomy survive and surprise.
Lockheed Martin has developed and demonstrated a
revolutionary approach to Collaborative Autonomy for Collaborative Autonomy is implemented by a Mission
heterogeneous teams of manned and unmanned vehicles Management system that provides the high levels of
[1]. The approach is specifically oriented to allow a team of intelligence necessary for autonomous and collaborative
unmanned vehicles to be commanded by a warfighter such mission operations. Autonomy lets teams of unmanned
as the CPG (Co-Pilot Gunner) of an Apache Longbow, who vehicles operate with only top-level human guidance and no
need for detailed supervision. Collaboration is essential for
team effectiveness.

Figure 2. The Five Key Attributes of Mission Management.

Collaborative Autonomy Architecture external to the team. This approach is more extensible and
The Collaborative Autonomy architecture is segmented into scalable.
seven major components (Figure 3):
The architecture is extensible because the components are
• Mission Planning – develops plans for the team and for decoupled; analysis and development can be performed by
individual vehicles different disciplines with relative independence.
Additionally, this means that novel algorithms can be added
• Collaboration – manages team formation and with a minimum disturbance of existing components.
interaction among team members Collaboration is an integral part of the system architecture –
that an entire component is dedicated to it and many
• Contingency Management – detects, assesses, and components have collaborative concepts at their core. For
responds to unexpected events example, mission planning is hierarchical in nature so
teams can be formed and reformed with tasks allocated and
• Situational Awareness – creates Common Relevant reallocated to team members. Contingency management is
Operating Picture (CROP) for team hierarchical in nature, supporting the concept of issues
being addressed at a team level. These team issues are
• Communications Management – Manages the addressed poorly in conventional approaches.
interaction with the vehicle’s communications systems.
The architecture is scalable, because collaboration has been
• Air Vehicle Management – Manages the air vehicle’s incorporated at the core of key components. The
flight systems, sensors, and weapons. architecture is intended to work with multiple instances of
itself so the team vehicles work synergistically and
• Resource Meta-Controller – Manages processing autonomously. Therefore, intermittent communication
resources and dynamically allocates them to different between instances or complete loss of an instance is
components as necessary. handled gracefully.

These components work in concert to achieve objectives
without violating constraints. This system architecture
offers substantial advantages over existing approaches, such
as recognizing the need to partition components requiring
distinct disciplines for analysis, development, and operation
as well as the need for autonomy to be collaborative both
with other autonomous systems of the team and systems

Collaborative Autonomy
Mission Management

Resource
Meta-Controller

Contingency Functional Modules
Management
Mission Planning

Situational Intelligent Agents
Awareness

Air Vehicle Management Collaboration Knowledge/Data
Communications Management Models

Air Vehicle Weapons/Sensors Communications
Flight Control System

DARRS025..ppt

Figure 3. Collaborative Autonomy is achieved through a Mission Management system made up
of a set of intelligent components that implement higher-level functions on top of the vehicle
systems.

Mission Planning capabilities), and vehicle/team and external asset capability
Mission Planning onboard the autonomous system performs information (e.g. payload availability and mobility models)
pre-mission and dynamic in-mission replanning for the are used. Mission planning generates mission plans
collaborative team. Mission planning develops including travel plans, sensor plans, communications plans,
collaborative synchronized plans for sensor employment, and weapon plans. At the team level, task objectives and
flight paths, communications, and engagements. constraints are generated for lower level mission planning
to honor. It then accepts, combines, and deconflicts those
Generally, most existing mission planning systems are plans when lower level mission planning responds.
monolithic in nature. These systems are very good at
planning for specific situations that are predetermined, but Collaboration
are poor reacting to unforeseen events. Unfortunately, it is Collaboration, i.e. the ability of multiple vehicles to interact
unrealistic for a mission planning system to have planners to carry out a team mission, is inherent in the Collaborative
to handle all situations and all contingencies. To address Autonomy architecture. Most components, including
these shortcomings, Lockheed Martin has developed a Mission Planning, Contingency Management, Situational
revolutionary approach to handle this problem via the Awareness, and Communications Management are
Mission Planning Toolkit [2]. In this toolkit, planning designed to facilitate the collaborative operations of a team
algorithms are broken down into their smallest functional of vehicles.
subcomponents, called “primitives”. The algorithm
primitives are then collected into a library of modules, each The Collaboration component embodies several functions
with specific inputs, outputs and functionalities. The toolkit (Figure 4) that are uniquely required in order to support this
is used to construct a specific planning system on the fly, operation. These include:
based on the current situational awareness. This allows for
the dynamic construction of mission planners, as opposed • Sharing Information and tasks
to just mission plans, to handle unpredicted events. For • Allocating Roles and Responsibilities
anticipated or common mission scenarios, reconstructed • Coordinating Task Execution
planner templates can be used for an even faster response • Dynamically forming teams
times. • Interacting with external assets
• Interacting with human Warfighter.
During operation, the Mission Planning Toolkit works in a
hierarchical fashion with mission plans at the highest level Two main technology elements of the Collaboration
– such as Teams A and B recon area ZEBRA, team plans at component are the Grapevine information sharing
the next level, and individual vehicle plans at the lowest technology, and the Dynamic team formation and
level. These plans optimize and/or account for factors such management.
as:
Grapevine information sharing [3] handles the aspects of
• High level mission objectives and constraints collaboration that deal with information sharing and
• Resource allocation for the number of vehicles coordination between unmanned team members, between
• Payload configuration for different mission objectives unmanned systems and the human Warfighter, and between
• Collaborative use of onboard sensors and external ISR the unmanned team and external systems such as C4ISR
and Networked Fires. On every unmanned vehicle, the
assets to detect, identify, and geo-locate vehicle and Collaboration component sets up intelligent agents known
dismounted infantry targets of interest as Proxies to represent each other manned or unmanned
• Communication events that support the teams' entity that vehicle needs to communicate with. Each Proxy
information dissemination and synchronization agent contains a set of criteria that are used to select and
requirements prioritize information for dissemination to the entity
• Routes that support the planned use of sensors and represented by the Proxy, known as the Client. The set of
communications while minimizing threat exposure Proxy agents are continually evaluating the information
• Target engagement planning and weapon deployment available to the Collaborative Autonomy system and
sequencing. selecting and prioritizing information for dissemination to
other manned and unmanned team members. The Proxy
Mission planning accepts objectives and constraints for agent’s criteria are updated in response to changing
planning missions as well as alerts indicating that conditions, such as new team members, changes in team
replanning is required. Geographic information (e.g. terrain, member roles, or changes in mission tasking, and can also
obstacle, and cultural), environmental information (e.g. be updated to reflect explicit requests for information from
weather), situational information (e.g. threat locations and a human Warfighter or external system.

SA Lead

• C4ISR Warf ighter
• Netw orked Fires Gatew ay

External • Status • Information
Asset • Plans Sharing
Gatew ay • CROP
• Command
Response

• C2 Handoff

Cooperative Sharing Information
Engage ment Assigning Team Responsibilities

Team Lead Warfighter Interaction
Coordinating Tasks

External System Interaction

DARRS02 4..p pt

Figure 4. Collaboration performs the functions necessary to enable a team of unmanned vehicles
to function as a team of human warfighters.

One important aspect of the Grapevine is the sharing of Contingency Management
Situational Awareness information to form a Common A key challenge to successful autonomous operations is
Relevant Operational Picture (CROP) across the team. The detection and reaction to unplanned events that affect the
Collaboration component handles the information sharing execution of the vehicle system’s mission. Contingency
operations needed to construct the CROP, and the Management watches for unexpected influences that affect
Situational Awareness component does the information team plan success, such as payload failure, modified orders,
fusion and deconfliction necessary to assemble the shared new operational constraints, changing environmental
information into a CROP. conditions and other unexpected changes in the battlespace
(see Figure 5). It works with the Mission Planning
Dynamic Team Formation accommodates the formation component to generate an effective response to the
and reformation of unmanned vehicle teams as required to contingency so the mission can be continued.
meet the mission requirements. At the beginning of the
mission, the Collaboration component identifies the set of The Contingency Management component is implemented
team members required to meet the mission requirements, based on Lockheed Martin’s MENSA technology [4].
and these vehicles exchange information to set up a team. MENSA takes each new or updated mission plan and
Setting up a team includes determination and distribution to applies algorithms to identify plan dependencies and
all team members of the team membership, team structure, constraints. Based on these dependencies and constraints, it
and allocation of roles within the team. An important sets up monitoring agents to check for conditions that
element of the team is the allocation of roles to team violate those dependencies and constraints. During
members to perform responsibilities on behalf of the team, execution of the plan, these agents continually monitor
such as coordinating interaction with the human warfighter. available information to determine if their assigned
When a team member is lost or damaged, new team conditions are met. If the conditions are met, the agent
members become available, or when the mission changes, signals that the contingency has occurred and the reasons
the team members interact to reform the team and reallocate about the impact of that contingency on the mission plan. If
roles. Reforming the team can include splitting the team necessary, the Mission Planning component is requested to
into two smaller teams to accomplish separate mission modify the plan to take into account the contingency.
tasks, or merging two or more teams into a single combined
team. For example, vehicle health updates are related to vehicle
operational capabilities (such as maximum endurance)
before being compared to the requirements of the executing

Failure by Needed Loss of Contact
External Asset With Operator(s)

Weather and Other
Environmental Factors

Loss/Failure
of Teammate

Vehicle System
or Payload
Failure

Unexpected Developments
in the Battlespace

Changes in Orders and
Operational Constraints

DARRS02 6..p pt

Figure 5. Contingency Management Handles Unexpected Influences that Affect Mission Plan
Success.

plan to determine if the vehicle can perform its mission as Contingency Management detects a contingency, assesses
planned. Pop-up threats are assessed with respect to their the impact and identifies a plan violation, then:
influence on the planned route that the vehicles will take
through threatened territory. This mission-centric approach 1. The affected vehicle locally performs a replan which
to contingency management focuses computational may resolve the problem
resources toward those problems that have real mission
impact and reduces the number of false alarms and 2. If there are tasks that could not be re-planned locally,
unnecessary replans that occur. contingency management then collaborates with other
team members to reallocate tasks
Contingency Management implements contingency
monitoring and plan impact analysis for most contingency 3. If there is a reallocation failure, a team replan is
types, including air vehicle flight capability degradation, triggered
pop-up threats and targets of opportunity, friendly and
neutral movement within the battle space, loss of team 4. If a team replan cannot resolve the situation,
members, and mission equipment failures. Contingency contingency management alerts the controlling element
Management can also determine when an emergency (typically a manned asset) of a team planning failure
mission abort is required and provides the controlling and awaits updated guidance.
element with control over the level/type of contingency
monitoring performed. Contingency Management takes in Situational Awareness
mission plans and information regarding the changing The Situational Awareness (SA) component gathers data on
situation (e.g. new objectives, new constraints, new the external tactical and environmental situation and
obstacles, new threats, new targets, and changes in processes it into a CROP, which the other Mission
vehicle/team capabilities). It issues alerts when plans will Management components use to make their decisions. A
no longer satisfy objectives and constraints. At the team pilot or crewmember needs good situational awareness to
level, it takes in alerts of contingencies that cannot be perform effectively in a manned system. Intelligent
handled at a vehicle level and issues alerts to team mission autonomous systems also require complete, timely, specific,
planning for replanning. and relevant information to make good “decisions”.

Our contingency management approach features a team- The Situational Awareness (SA) module is implemented by
wide contingency resolution escalation process where leveraging Lockheed Martin’s technology for Level 1 Data
Fusion [6] and Battlefield Assessment, originally developed
on the Rotorcraft Pilot’s Associate program. SA performs
multiple levels of assessment of the data [5] from onboard

C4ISR Netw ork

Situational Aw areness

Level 1 Level 3 • Mobility
Object Predictive • Intent
Assessment Battlespace
Aw areness

CROP With Selected Level 2 Level 4
Images
Situation Process
Assessment Ref inement

Cues, Sensor
Requests, Tracks

Environmental SA

Sensor Coverage SA
Lead
Clustering ID 2 • Threat
Intervisibility Team Shared
13 CROP
• Threat Priorities
2
• Obstacles
• Weather

Threat Relationships

DARRS02 3..p pt

Figure 6. Situational Awareness provides a comprehensive assessment of all battlespace information to
enable the Collaborative Autonomy functions to operate with precision information.

sensors and external data sources (Figure 6) to produce the components to make autonomous decisions that guide
CROP. Level 1 Object Assessment consists of fusing data vehicle behavior.
from onboard sensors, teammate sensors, and external data
sources such as C4ISR networks to produce a set of tracks Air Vehicle Management
representing friendly and threat entities in the battlespace. Air vehicle management (AVM) provides the link between
In addition to this fusion, SA deconflicts data from each of the Collaborative Autonomy components and the vehicle
the teammates to ensure that each vehicle’s CROP is systems. It translates tasks from the Mission Planner into
consistent. commands for the vehicle sensors, weapons, and flight
systems and acts as the point of entry for information from
Level 2 Situation Assessment consists of evaluating the these vehicle systems into Mission Management.
fused track picture in the CROP to assess friendly and
threat sensor coverage and intervisibility, potential threat AVM refines route plans to minimize overall exposure to
organizations, and the priority associated with different threats factoring in terrain masking, collision risks and
threats. Level 3 Predictive Battlespace Awareness [7] vehicle dynamics. AVM provides reflexive obstacle and
determines likely threat mobility and future locations, and threat response capability to enhance overall system
assesses likely threat intent. Level 4 Process Refinement survivability. AVM quickly maneuvers the vehicle out of
determines when the information being produced by harm’s way while the more deliberative system autonomy
Situational Awareness does not meet the requirements of generates a re-plan to achieve mission objectives. AVM
the mission, and takes action to generate additional generates trajectory commands based on a library of
information such as requesting Mission Planning to task maneuver primitives, including agile maneuvers that fully
sensors, from other vehicles, or from the C4ISR networks. span the available flight envelope, providing enhanced
maneuvering effectiveness for survivable threat response.
In addition to this multi-level processing of sensor AVM accepts travel plans (e.g. flight plans), threat
information, Situation Awareness collects and maintains warnings from onboard sensors, and obstacle warnings
other types of information such as weather data, from obstacle sensors and generates maneuvers to the
environmental information, and obstacle maps. This vehicle actuator systems.
information is also used by Mission Planning and other

As part of plan refinement, the Mission Planning generates Management is shown in Figure 7.
routes between mission “hard points” that minimize the
total exposure to known external threats by factoring in the Resource Meta-controller
threat type, location, lethality radius, terrain elevation Resource Meta-controller (RMC) is a software
profiles, and the vehicle’s exposure given its position, infrastructure component providing processing and memory
speed, and attitude. The route plan is then refined within the resources for other components. RMC operates in concert
route plan constraints to further reduce threat exposure, with operating system level resource management
generating detailed flight trajectories that adjust speed, functions. RMC performs system management functions
aspect angles, and altitude above the local terrain to reduce such as processor switchover, memory zeroize, pre- and
the total risk of exposure to external threats. The plan post-mission data exchange and fault isolation. RMC
refinement component of AVM produces trajectories that manages computational resources by performing resource
meet the route plan goals and constraints, while reducing utilization monitoring, resource allocation to agents,
the exposure to risk from external threats and terrain resource reclamation and reallocation, resource tracking,
collisions. and resource scheduling and optimization. The RMC Agent
Supervisor manages agents by agent creation and
Communications Management destruction, agent registration and monitoring, job
Communications Management provides and manages data assignment and status reporting, and agent suspension and
links to connect team members with each other and with resumption. RMC provides other components with access
external assets (e.g., ISR and Networked fires) over to data by managing publication/subscription interchanges,
battlefield networks. Communications software manages managing data retention and performing structured queries
this system by: implementing the communications plan upon request.
provided by mission planning using available system data
links, predicting and monitoring communication Quality of Implementation
Service (QoS) and optimizing performance of the data Mission Management is the component that provides the
links. Communications may also request Mission Planning intelligence for the unmanned team to make collaborative
to modify plans to keep QoS at effective levels. The and autonomy decisions. The architecture for the Mission
relationship between Collaboration and Communications Management segment was instantiated in the

Comm HW Comm Collaboration Mission
Manager SW Services Management
• Encryption
• LPI/LPD • Message • Team Mission
Formatting Manage ment Plann ing
Wav ef orms
• Modulation/ • Netw ork • Information Situational
Manage ment Dissemination/ Aw areness
Demodu lation Routing
• Signal • Flow Control Contingency
• Hardw are • Information Manage ment
Transmission Prioritization
• BIT Control
• Hardw are • Proxy/Gateway
Protocols
Interf ac e
• Error • Negotiation
Protocols
Manage ment

DARRS022..ppt

Figure 7. Communications Management and Collaboration interact to ensure that needed
information is exchanged among team members and with external systems.

Manned/Unmanned (MUM) Teaming Demonstration that representative system for evaluations and performance
verified the high levels of intelligence necessary for analysis, forming a robust test bed that accommodates a
autonomous and collaborative mission operations can be number of changes into the environment and assesses the
achieved. Autonomy lets the vehicle operate with only top- capability of the manned/unmanned team to respond to the
level human guidance and no need for detailed supervision. changes. The demonstration showed that the combination of
Collaboration is essential for team effectiveness. manned and unmanned team attack assets provided a new
level of situational awareness and operational flexibility not
The MUM Teaming demonstration showcased critical currently available.
concepts including autonomy and collaborative operations,
Human Machine Interface (HMI) and workload A representation of the MUM teaming demonstration is
management approaches and technologies, and manned shown in Figure 8.
unmanned system interaction. The MUM Demonstration
created a high fidelity simulation-driven test bed to develop The demonstration culminated in an exercise where an
and evolve MUM concepts and to mature the autonomy and independent team injected a number of changes into the
collaborative technology. The simulation showcased the simulation environment and assessed the capability of the
robustness of the MUM approach by responding to manned/unmanned team to respond in an autonomous and
contingency behaviors and by providing a new level of collaborative manner to the changes. The results of the
situational awareness and operational flexibility. The MUM teaming demonstration were exciting and
simulation was an evolutionary development of increasing convincing. The HMI approach, including spoken language
fidelity over time to demonstrate autonomous and systems voice command and response, provided a natural
collaborative operations and assess the technical feasibility communication modality for the MUM team commander.
of achieving this capability. The team-based mission management, collaborative
autonomy algorithms, and system implementation clearly
The MUM Teaming demonstration contained a team of showed the advantages and possibilities in team based
simulated rotary wing vehicles commanded from either a operations with highly intelligent vehicles. The Advanced
ground command console or a manned aircraft, represented Tactical Combat Model (ATCOM) simulation results
as a simulated Apache Longbow. The testbed also utilized the dynamic re-planning and contingency response
incorporated command and control nodes, Command, available in the MUM Teaming Demonstration. Finally, the
Control, Communications, Computers, Intelligence, demonstration showed that the combination of manned and
Surveillance, and Reconnaissance (C4ISR) network, and unmanned team attack assets provided a new level of
threats, in addition to the human machine interfaces and situational awareness and operational flexibility not
information exchanges between these simulated currently available.
components. The simulation environment provides a

C4ISR NET / GIG

Air Team Commander Team of Unmanned
Vehicles

Threats

HQ

Ground Team
Commander

Figure 8. MUM Teaming Demonstration.

The Air Team Commander is a member of a team Acknowledgments
containing unmanned vehicles (UVs) and provides mission Some of the work described in this paper was funded under
redirects to the UVs, receives/dispositions target the OTA portion of the DARPA Unmanned Combat Armed
engagement requests, and receives vehicle status/mission Rotorcraft (UCAR) program (MDA972-02-9-0011). The
plans. The team commander had high fidelity controls and authors wish to recognize the following individuals who
on-board displays to control the UV team. These have made recent contributions to this system:
capabilities include: tactile vest, spoken language system,
and multi-purpose display pages with a digital map. The Draper Laboratory – Brent Appleby, Mark Homer, Leena
Ground Team Commander is used with the unmanned Singh, Lee Yang, and their team
vehicles to ensure that the vehicles are prepared for the
mission and execution of the initial and final portions of the Lockheed Martin Advanced Technology Laboratory -
mission. David Cooper, Rich Dickinson, Chris Garrett, Adria
Hughes, Mike Orr, Brian Satterfield, Mike Thomas, and
The simulation included software-in-the-loop execution of Vera Zaychik
critical team-based mission planning, autonomy,
collaboration and contingency management functions. The Lockheed Martin Simulation Training and Support – Ken
system included a six degree-of-freedom air vehicle model. Stricker and Brian Vanderlaan
The system implemented reflexive maneuver elements of
the air vehicle management system and collaborative team Lockheed Martin Systems Integration – Owego – Erin
searches and target engagements with weapons release Accettullo, Rick Crist, Steve DeMarco, Dave Garrison, Carl
authority provided by the manned element. The system Herman, Adam Jung, Ateen Khatekhate, John Moody,
explored key aspects of the HMI solution, which included Donn Powers, Greg Scanlon, Mike Scarangella, Keith
spoken language system voice command and response, Sheppard, Tom Spura, Peter Stiles, and Joel Tleon
tactile vest for alerting, mission controls and displays
integrated with existing systems, and workload UCAR Government Team - Bob Boyd, Marsh Cagle-West,
management functions, including negotiated intervention. Steve MacWillie, Steve Rast, Randy Scrocca, CW4 Matt
Thomas, and Don Woodbury
A distributed team was responsible for the demonstration:
Lockheed Martin Systems Integration - Owego, Lockheed References
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