Terminology for Specifying the 

Autonomy Levels for Unmanned 

Systems: Version 1.0

Edited by: Hui-Min Huang

NIST Special Publication 1011
NIST Special Publication 1011

Terminology for Specifying the 

Autonomy Levels for Unmanned Systems: 

Version 1.0 

Edited by: Hui-Min Huang

Intelligent Systems Division

Manufacturing Engineering Laboratory

January 2004

U.S. Department of Commerce

Donald L. Evans, Secretary

Technology Administration

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National Institute of Standards and Technology

Hratch G. Semerjian, Acting Director 
Certain commercial entities, equipment, or materials may be identified in this 

document in order to describe an experimental procedure or concept adequately. Such 

identification is not intended to imply recommendation or endorsement by the 

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entities, materials, or equipment are necessarily the best available for the purpose.

National Institute of Standards and Technology Special Publication 1011

Natl. Inst. Stand. Technol. Spec. Publ. 1011, 32 pages (April 2004)

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1 

Terminology for Specifying 

the Autonomy Levels for Unmanned Systems 

Version 1.0 

Contributed by the Federal Agencies Ad Hoc Autonomy Levels for 

Unmanned Systems Working Group Participants1

Edited by: Hui-Min Huang 

National Institute of Standards and Technology

April 2004 

 

1

 See list for Contributors. 
2 

EXECUTIVE SUMMARY 

This document, produced by the Federal Agencies Ad Hoc Autonomy Levels for Unmanned 

Systems (ALFUS) Working Group (WG), defines and collects the terminology to support the 

Group’s main objective, the definitions of the unmanned system autonomy levels and the metrics 

for measuring the autonomy levels. 

The WG consists of, and was founded by, unmanned systems professionals from government 

agencies and their supporting contractors2

 on a voluntary basis. The WG output is based on 

Group consensus. In its first workshop, held on July 18, 2003, the Group has decided to launch 

an effort to produce a framework for autonomy level definitions and metrics. A committee, 

composed of six participants and representing different application domains, was formed and 

charged to draft the framework. Also decided was that the first version of the framework should 

focus on supporting the first client of this working group effort, the Army Future Combat 

Systems (FCS) program. 

The WG determined, at the second workshop, held on September 11, 2003, that terminology 

should be the first part of the to-be-developed initial framework. The terms should be defined in 

a generic way to support unmanned vehicles of various domains, including aerial, ground, and 

water. In this version of the document, we attempt to maintain the generic nature of the terms as 

well as to support the specific program, FCS. 

The approaches in this terminology effort are: 

• Leverage existent work and adopt existent definitions given in relevant references. This 

would expedite the Group’s effort in proceeding with its core objective, the autonomy 

level model. The references are listed at the end of this document. Modifications to the 

existent definitions may be necessary3

 to fit the objectives of this working group. 

• Consider the cultural factor, for example, how people are using the terms, to ensure a 

seamless transition of the outcome to the users. 

• Consolidate similar terms and resolve conflicting ones. 

• Some terms may have generic and widely applicable definitions but are further defined 

for specific domains. We may provide both their generic definitions, in the GENERIC 

TERMS AND DEFINITIONS section, and their extensions in the DOMAIN SPECIFIC 

TERMS OR EXTENSIONS section. There are also terms that are only applicable to 

specific domains. They are defined in the DOMAIN SPECIFIC TERMS OR 

EXTENSIONS section, as well. Further efforts are needed to enhance this 

categorization. 

• Derived terms are not redefined but are cross-referenced to the definition for the root 

term. 

 

2

 The WG will be open to all the interested professionals at a later stage. 

3

 There are several cases when the definitions contributed by our WG members are similar to those given in 

the existent references. The descriptions from the existent references were typically adopted as the basis but 

enhanced by Members’ contributions. 
3 

Version 0 of the document, from NIST and the working committee, was presented and discussed 

in the second workshop. Additional terms were identified, which were assigned to the 

participants for definitions. Numerous further iterations have been conducted with the working 

group participants and user communities thereafter. This draft has all the contributions 

incorporated. The plan is to finalize Version 1 of this document by January 2004 for the FCS. 

Since the working group has adopted a spiral development approach, this document is fully 

anticipated to evolve alongside the autonomy level framework itself. Readers and user 

communities have been, and are continuously encouraged to provide feedback. 

Please address feedback to: 

Hui-Min Huang 

National Institute of Standards & Technology 

Bldg. 220 Rm. B124 

100 Bureau Drive, Stop 8230 

Gaithersburg, MD 20899-8230 

Tel: 301 975-3427 

Fax: 301 990-9688 

Email: hui-min.huang@nist.gov 
4 

TABLE OF CONTENTS 

EXECUTIVE SUMMARY .................................................................................................... 2 

AUTHORING COMMITTEE................................................................................................ 5 

CONTRIBUTORS ................................................................................................................ 5 

VERSION HISTORY............................................................................................................ 6 

INTRODUCTION................................................................................................................. 7 

GENERIC TERMS AND DEFINITIONS............................................................................... 9 

DOMAIN SPECIFIC TERMS OR EXTENSIONS ................................................................ 22 

APPENDIX A. TO-DO LIST.............................................................................................. 23 

APPENDIX B: ACRONYMS ............................................................................................. 25 

REFERENCES ................................................................................................................... 29 
5 

AUTHORING COMMITTEE 

Bruemmer, David—DOE INEEL4

Ferlis, Robert—DoT FHWA 

Huang, Hui-Min—NIST 

Novak, Brian—U.S. Army TACOM 

Schultz, Alan C.—U.S. Navy NRL 

Smith, Robert—U.S. Air Force AFRL 

CONTRIBUTORS 

Adams, Curt—U.S. Army TACOM 

Albus, James—NIST 

Antonishek, Brian—NIST 

Arthur, Keith—U.S. Army AATD 

Barbera, Anthony—NIST 

Barnhill, Robert MAJ—U.S. Army 

Brendle, Bruce—U.S. Army TACOM 

Bruemmer, David—DOE INEEL 

Cagle-West, Marsha—U.S. Army AMRDEC SED 

Cerny, Jeffrey—U.S. Army AMRDEC-ASD 

Clough, Bruce—U.S. Air Force AFRL 

Dzugan, Mike—U.S. Army CERDEC 

English, Woody—U.S. Air Force AFRL Support 

Ferlis, Robert—DoT FHWA 

Gage, Doug—DARPA 

Gage, Gerrie LTC—DARPA 

Higgins, Ray—U.S. Army AATD 

Hirtz, Julie—U.S. Army DCD 

Hodge, Kelley A. MAJ—U.S. Army 

Huang, Hui-Min—NIST 

Juberts, Maris—NIST 

Knichel, David— U.S. Army DCD 

Kotora, Jeffrey—OSD Support (Titan) 

Mamplata, Caesar G.—U.S. Navy NAVAIR 

Messina, Elena—NIST 

Novak, Brian—U.S. Army TACOM 

Overstreet, Dennis—DARPA Support (SRS Tech) 

Rovegno, John COL—U.S. Army 

Pavek, Kerry— U.S. Army UAMBL (Titan) 

Scholtz, Jean—NIST 

Schultz, Alan C.—U.S. Navy NRL 

Scott, Harry—NIST 

Shoemaker, Charles— U.S. Army ARL 

Smith, Robert— U.S. Air Force AFRL 

Wavering, Albert—NIST 

Wit, Jeffrey— U.S. Air Force AFRL Support

 

4

 See APPENDIX B: ACRONYMS. 
6 

VERSION HISTORY 

• Draft Version 1.0—Accommodated comments raised in the Workshop #3, distributed on 

December 11, 2003. 

• Draft Version 0.9—Distributed to members and user community on October 25, 2003, 

redistributed on November 10, 2003. 

• Draft Version 0.7—Distributed to members and user community for feedback at the end of 

September 2003. 

• Draft Version 0—Presented and discussed in Workshop #2, September 11, 2003. 
7 

INTRODUCTION 

Unmanned systems have been fielded in several domains in the recent past, ranging from 

battlefields to Mars and mostly sponsored by the Government. As the number of programs for 

developing unmanned systems accelerates, there is a growing need for characterizing these 

systems. Individual government agencies have begun these efforts. The Department of Defense 

Joint Program Office, the Air Force Research Laboratory, the U.S. Army Science Board, the 

Army Maneuver Support Center, and National Institute of Standards and Technology have 

described levels of autonomy for various programs [2, 28, 29, 30, 31]. NASA has embarked 

upon a project on defining levels of autonomy for a human space flight vehicle [32]. It is 

beneficial that these and other agencies leverage each other’s efforts and aim at a consistent 

approach. 

This incentive gives rise to the Federal Agencies Ad Hoc Autonomy Levels for Unmanned 

Systems (ALFUS) Working Group. The Group’s objectives are to define methods for 

establishing metrics for autonomy and to draft a framework for autonomy levels for unmanned 

systems (ALFUS). The Group determined that a beginning step would be to identify and define a 

set of terms that may be needed to support the framework development effort. The terms should 

include a set that is generic and applicable to unmanned vehicles of various domains and another 

set that is domain specific, including extensions to the generic terms. 

The workshop participants identified the terms based on such premises. However, it is possible 

that, after further investigation, some of the terms currently identified as generic might be 

reassigned to the domain specific section. Some other terms might even be considered beyond 

the scope of the autonomy level definition. It is also understood that additional terms may be 

included as the working group efforts proceed further. We plan to continue updating this 

document and addressing these issues in the future versions. 

Several format and structural notes: 

1. Terms are listed in alphabetical order. Terms that have the same roots are grouped together 

and defined to facilitate consistent definitions. These terms also appear according to their 

original alphabetical order without being redefined. 

2. Boldface is used to indicate the terms defined in this document. When used in defining other 

terms, a term is hyperlinked to its original definition in the electronic version of the 

document. 

3. On the different types of references, we use: 

• braces, { }, to indicate that the definition is adopted, i.e., a direct cut-and-paste or close to 

it, from the cited reference, 

• brackets, [ ], to relate the stated definitions to the cited reference(s), and 

• angular brackets, < >, to point to ongoing discussions, potential future expansions, 

unresolved issues, etc., as described in APPENDIX A. TO-DO LIST. 

Note that footnotes are indicated with numbers in superscript. 

4. Multiple definitions, obtained either from multiple references or through members consensus, 

may be given to a term when necessary. They are indicated with (A), (B), (C) ... . 
8 

5. APPENDIX B: ACRONYMS facilitates both the definition of the Terms and the autonomy 

level framework itself. 
9 

GENERIC TERMS AND DEFINITIONS 

Adapt to Failures and Operational Conditions. 

An unmanned system experiencing either system failures or operational conditions that 

prevent it from continuing its optimal mission profile will react within the confines of its 

capabilities. Adaptation with respect to capabilities includes hover, orbit, stop, and station 

keeping. This adaptation is performed by the system until the condition is cleared or by the 

operator. System requirements may mandate that the unmanned system continue to perform 

the mission in a degraded mode. 

Autonomous. 

Operations of an unmanned system (UMS) wherein the UMS receives its mission from the 

human <1> and accomplishes that mission with or without further human-robot interaction 

(HRI). The level of HRI, along with other factors such as mission complexity, and 

environmental difficulty, determine the level of autonomy for the UMS [2]. Finer-grained 

autonomy level designations can also be applied to the tasks, lower in scope than mission. 

Associated terms: 

Fully autonomous. See under Mode of Operation.

Semi-autonomous. See under Mode of Operation.

Autonomous Collaboration. 

The ability of a UMS to collaborate with one or more manned vehicles or UMS without 

the need for an external controlling element.

Autonomy. 

(A) The condition or quality of being self-governing {1}. 

(B) A UMS’s own ability of sensing, perceiving, analyzing, communicating, planning, 

decision-making, and acting, to achieve its goals as assigned by its human operator(s) 

through designed HRI. Autonomy is characterized into levels by factors including 

mission complexity, environmental difficulty, and level of HRI to accomplish the 

missions. 

Associated terms: 

Autonomy Level or Level of Autonomy. 

Set(s) of progressive indices, typically given in numbers, identifying a UMS’s capability 

for performing autonomous missions. Two types of metrics are used, Detailed Model 

for Autonomy Levels and Summary Model for Autonomy Levels. 

Autonomy Levels for Unmanned Systems (ALFUS). 

A general term referring to the autonomy level framework, models, and the level 

numbers. 
10 

Detailed Model for Autonomy Levels. 

A comprehensive set of metrics that represent multiple aspects of concerns, including 

mission complexity, environmental difficulty, and level of HRI that, in combination, 

indicate a UMS’s level of autonomy. This model corresponds to the Summary Model 

for Autonomy Levels. 

Summary Model for Autonomy Levels. 

A set of linear scales, 0 through 10 or 1 through 10, indicating the level of autonomy of a 

UMS. This model is derived from the UMS’s Detailed Model for Autonomy Levels.

Built-in Test. 

Equipment or software embedded in operational components or systems, as opposed to 

external support units, which perform a test or sequence of tests to verify mechanical or 

electrical continuity of hardware, or the proper automatic sequencing, data processing, and 

readout of hardware or software systems. 

Classes of UGVs. The JRP postulates several classes of UGVs, based on weight {2}, <3>: 

• Micro: < 8 pounds5

• Miniature: 8-30 pounds 

• Small (light): 31-400 pounds 

• Small (medium): 401-2,500 pounds 

• Small (heavy): 2,501-20,000 pounds 

• Medium: 20,001-30,000 pounds 

• Large: >30,000 pounds. 

Cognizance Levels or Levels of Cognizance. 

The levels of what a UMS can know or understand based on its sensory processing

capability: 

• Level 1 – data, or observed data. In initially processed forms after measured by sensors. 

• Level 2 – information. Further processed, refined and structured data that is human 

understandable. 

• Level 3 – intelligence, knowledge, combat and actionable information. Further processed 

for particular mission needs. Directly linked to tactical behaviors. 

Collaboration or Cooperation. 

The process by which multiple manned or unmanned systems jointly work together by 

sharing data, such as coordinates of their maneuver(s) and local Common Relative 

Operational Picture (CROP), or by acquiring intelligence to perform a mission

synergistically, i.e., perform better than each could have alone <2>. 

Associated term:

 

5

 NIST endorses SI units. However, since the definition is adopted, in its entirety, from the cited reference, 

the usage of British units is retained. 
11 

Coordination. 

The ability for UMS’s or manned systems to work together harmoniously through 

common data such as mission or task plans, coordinates of maneuver(s), local CROP, etc. 

A common way is for a superior to coordinate the task execution of the subordinates to 

accomplish the missions [1, 3]. 

Control Level or Level of Control. <10>

Controlling Element. 

The part of a UMS that provides a method for a human to control it remotely. 

Cooperation. See Collaboration. 

Coordination. See under Collaboration.

Data Fusion. See Fusion. 

Detailed Model for Autonomy Levels. See under Autonomy.

Dynamic mission planning. See mission planning. 

Environment. 

Used as a general reference, environment includes the generic, natural conditions; e.g., 

weather, climate, ocean conditions, terrain, vegetation, etc. Modified environment can refer to 

specific induced environments; e.g., dirty battlefield environment, nuclear-chemicalbiological environment, etc. Environment includes those conditions observed by the system 

during operational use, standby, maintenance, transportation, and storage. Mission 

environment includes threat situation or Electronic Order of Battle (EOB), Rules of 

Engagement (ROE), Emission Condition (EmCon), etc.

Fault Tolerance. 

The ability of a system or component to continue normal operation despite the presence of 

hardware or software faults {14}. 

Fully autonomous. See under Mode of Operation.

Fusion. Also referred to as Information Fusion or Data Fusion. 

(A) The combining or blending of relevant data and information from single or multiple 

sources (sensors, logistics, etc.) into representational formats that are appropriate to support 

the interpretation of the data and information and to support system goals like recognition, 

tracking, situation assessment, sensor management, or system control. Involves the process of 

acquisition, filtering, correlation, integration, comparison, evaluation and related activities to 

ensure proper correlations of data or information exist and draws out the significance of those 

correlations [6, 7]. The processes can be performed with a combination of human 

analysis/judgment and system processing. 
12 

(B) Information processing that deals with the association, correlation, and combination of 

data and information from single and multiple sources to achieve refined position and identity 

estimation, complete and timely assessments of situations and threats, and their significance 

in the context of mission operation. The process is characterized by continuous refinement of 

its estimates and assessments, and by evaluation of the need for additional sources, or 

modification of the process itself, to achieve improved results [8]. 

Fusion Levels or Levels of Fusion. 

Each of the six levels of fusion adds progressively greater meaning and involves more 

analysis {9} [5]: 

• Level 0 - organize. This is the initial processing accomplished at or near the sensor that 

organizes the collected data into a usable form for the system or person who will receive 

it. 

• Level 1 - identify/correlate. This level takes new input and normalizes its data; correlates 

it into an existing entity database, and updates that database. Level 1 Fusion tells you 

what is there and can result in actionable information. 

• Level 2 - aggregate/resolve. This level aggregates the individual entities or elements, 

analyzes those aggregations, and resolves conflicts. This level captures or derives events 

or actions from the information and interprets them in context with other information. 

Level 2 Fusion tells you how they are working together and what they are doing. 

• Level 3 - interpret/determine/predict. Interprets enemy events and actions, determines 

enemy objectives and how enemy elements operate, and predicts enemy future actions 

and their effects on friendly forces. This is a threat refinement process that projects 

current situation (friendly and enemy) into the future. Level 3 Fusion tells you what it 

means and how it affects your plans. 

• Level 4 - assess. This level consists of assessing the entire process and related activities 

to improve the timeliness, relevance and accuracy of information and/or intelligence. It 

reviews the performance of sensors and collectors, as well as analysts, information 

management systems, and staffs involved in the fusion process. This process tells you 

what you need to do to improve the products from fusion level 0-3. 

• Level 5 - visualize. This process connects the user to the rest of the fusion process so that 

the user can visualize the fusion products and generate feedback/control to 

enhance/improve these products. 

Goal. 

A result (or state) to be achieved or maintained [3]. 

Hazard Avoidance. 

Similar to obstacle avoidance except that the subjects are not limited to physical objects but 

also include adversarial situations, as either assessed by the UMS’s perception functions or 

provided through the HRI, that are to be avoided. 

Human/Operator Intervention. 

The need for HRI in a normally fully autonomous behavior due to some extenuating 

circumstances. An unanticipated action or input by the user to help complete a task. 
13 

Human robot coordination. See coordination. 

Human Robot Interaction/Interface (HRI). Also referred to as human interaction or 

operator interaction. 

(A) The activity by which human operators engage with UMSs to achieve the mission 

goals. 

(B) The architecture for interaction between the robot and the human. It includes the 

specification of the interaction language: what tasks the user can ask of the robot and 

the corresponding actions, what tasks the robot can ask of the user and the corresponding 

actions. It is independent of a particular display or interaction modality. It is the 

planned and anticipated interactions between the robot and the user. 

(C) Human Robot Interface is further used to reference the physical realization of the 

method of Human Robot Interaction or Intervention.

The following are the different roles of interaction possible for the human in HRI <4>. Note 

that one person could possibly assume a number of roles or numerous people could take 

individual roles or even share roles. The user interface should be based on the types of roles 

the user will assume. In addition to specific information needed for each role, the user will 

need some awareness of other roles simultaneously interacting with the robot. 

Supervisor – the supervisor monitors one or more robots with respect to progress on the 

mission, can task the robot(s) at the mission level, monitors mission progress, provides 

mission level directions, coordinates missions, and can assign an operator to assist a robot if 

needed. 

A commander would be an example of a person who performs the supervisor-only role. 

Teammate/Wingman – this is considered to be a human team member. UMS and its 

teammate each performs part of the overall mission and they coordinate when needed. The 

teammate may command the UMS at the levels of detail of tasks or task plans. 

Operator – the role assumed by the person performing remote control or teleoperation, 

semi-autonomous operations, or other man-in-the-loop types of operations. The operator 

input is expected at certain states during normal operations. During error conditions, the 

operator determines the problem that a robot is experiencing in interacting with the physical 

world, interacts with the robot to solve this if possible and returns control to the supervisor 

with an outcome, successful or not. If the operator cannot overcome the problem it may be 

necessary to pass the robot control to the mechanic. 

Mechanic or Developer – determines the problem with the hardware or software that the 

robot is having, solves this if possible, may interact with the robot to test out the proposed 

solution, and returns control of the robot to the supervisor with a determination. 

Bystander – coexists in the same environment as the UMS but with an unknown role. The 

bystander role could be neutral, friendly, or adversarial, or include various combinations. 

The bystander and the UMS need to build up some expectation of what the counterpart will 

do in order to react accordingly. For example, the driver, a bystander, of a car may have to 
14 

interact at a four way stop with a UMS. They both need some indication as to whether the 

other vehicle knows the rules of the road. 

Pedestrians and traffic police would be examples of bystanders who would have limited 

interaction with autonomous driving vehicles. UMS needs to be able to protect itself from 

possible harm from adversarial bystander. 

Human Operated. 

The type of HRI that refers to remote control or teleoperation. 

Human Assisted. 

The type of HRI that that refers to situations during which human interactions are needed at 

the level of detail of task plans, i.e., during the execution of a task. 

Human Delegated. 

The type of HRI that refers to situations during which human interactions are mainly at the 

task level. 

Human Supervised. 

The type of HRI that refers to situations during which humans play the monitoring role and 

human interactions are mainly at the mission level. 

Information Fusion. See Fusion. 

Leader Follower. See Robotic Follower. 

Markers (physical or electronic). 

A visual or electronic aid used to mark a designated point for such tactical purposes as route 

following, determination of bearings, courses, or location, and key items or points of interest, 

including landmine markers, minefields markers, and area NBC decontamination markers. 

Traffic signs and signals are additional examples of Markers. 

Methods of Control. 

The interface, either software or hardware, such as a joystick, waypoint selection via a map 

interface, natural language, hand signals, etc., that operators use to control a UMS.

Mission. 

The highest-level task assigned to the UMS {3}. 

Mission Module. 

A self-contained subsystem installed on a UMS that enables the UMS to perform designed 

missions. It can be easily installed and replaced by another type of mission module [2]. 
15 

Mission Planning. 

The process to generate tactical goals, a route (general or specific), commanding structure, 

coordination, and timing for one or teams of UMSs. The mission plans can be generated 

either in advance by operators on an OCU or in real-time by the onboard, distributed 

software systems. The latter case is also referred to as dynamic mission planning [2, 3].

Mobility. 

The capability of a UMS to move from place to place, with its own power and while under 

any mode or method of control. Characteristics: the UMS’s speed, location, and fuel 

availability [2]. Refueling could be performed either as a part of the HRI or autonomously by 

a fuel management autonomy task at a higher level. 

Mode of Operation or Operational Mode. 

Human operator’s ability to interact with a UMS to perform the operator assigned missions. 

The following are the defined modes of operation: fully autonomous, semi-autonomous, 

teleoperation, and remote control. 

Associated terms: 

Fully autonomous. 

A mode of operation of an UMS wherein the UMS is expected to accomplish its 

mission, within a defined scope, without human intervention. Note that a team of UMSs 

may be fully autonomous while the individual team members may not be due to the 

needs to coordinate during the execution of team missions.

Semi-autonomous. 

A mode of operation of a UMS wherein the human operator and/or the UMS plan(s) and 

conduct(s) a mission and requires various levels of HRI [2] <6>. 

Teleoperation. 

A mode of operation of a UMS wherein the human operator, using video feedback 

and/or other sensory feedback, either directly controls the actuators or assigns 

incremental goals, waypoints in mobility situations, on a continuous basis, from off the 

vehicle and via a tethered or radio linked control device [2]. In this mode, the UMS may 

take limited initiative in reaching the assigned incremental goals. 

Remote control. 

A mode of operation of a UMS wherein the human operator, without benefit of video or 

other sensory feedback, directly controls the actuators of the UMS on a continuous basis, 

from off the vehicle and via a tethered or radio linked control device using visual line-ofsight cues {2}. In this mode, the UMS takes no initiative and relies on continuous or 

nearly continuous input from the user.
16 

Observation. 

(A) The information collection stage of the "OODA Loop" (Observation, Orientation, 

Decision, Action)6 

(B) Measurement of the environment by sensors that produce signals that can be analyzed. 

Obstacle. 

(A) Any physical entity that opposes or deters passage or progress, or impedes mobility in 

any other way [12]. 

(B) Any obstruction designed or employed to disrupt, fix, turn, or block the movement of an 

opposing force, and to impose additional losses in personnel, time, and equipment on the 

opposing force. Obstacles can be natural, manmade, or a combination of both. [13] They can 

be positive, negative (e.g., ditches), or groupings (e.g., areas with high security alert) and can 

be moving or still <5>. 

Operational Mode. See Mode of Operation.

Operator Control Unit (OCU). 

Also referred to as operator control interface (OCI) or human interaction control unit. 

The computer(s), accessories, and data link equipment that an operator uses to control, 

communicate with, receive data and information from, and plan missions for one or more 

UMSs {2}. 

Orientation. 

(A) The stage in the OODA loop (Observation, Orientation, Decision, Action) that involves 

analysis and prediction and generates information to support decision making stage 

(B) Rotational displacement between two coordinate frames of reference. 

Perception. 

A UMS’s capability of sensing and building an internal model of the environment within 

which it is operating, and assigning entities, events, and situations perceived in the 

environment to classes. The classification (or recognition) process involves comparing what 

it observed with the system’s a priori knowledge7

 [3]. 

Associated term: 

Local perception. 

When the perception process has occurred locally onboard the UMS and is regarding the 

UMS’s local environment and within the UMS’s mission context. 

Perception Levels or Levels of Perception [3]. 

The progressive results of sensory information after the data have gone through multiple 

levels of sensory processing: 

 

6

 Conceived by Col. John R. Boyd in the 1970s as an air-to-air combat strategy for military fighter pilots. 

7

 Similar to the combination of Observation and Orientation as used in ACL. 
17 

• Level 1 – point or pixel. A point of concern has physical properties that, quantitatively, 

can be either measured with the systems’ sensor(s) in a one-to-one correspondence or 

computed over time and space. 

• Level 2 – line or list. Groupings of sets of points according to certain criteria, such as 

continuity in position and direction, over space and/or time. 

• Level 3 – surface or boundary. Groupings of sets of contiguous lines or lists according to 

certain criteria, such as continuity in orientation or curvature, over space and/or time. 

• Level 4 – object. Groupings of sets of contiguous surfaces and boundaries according to 

certain criteria, such as rigid body mechanics, over space and/or time. 

• Level 5 – unit of objects. Groupings of sets of objects according to certain criteria, such 

as density, distribution, and relative positions, motions, and interactions, over space 

and/or time. 

Point Man or Unmanned Point Man, Robotic Point Man. 

(A) A human (soldier in the military domain) assigned some distance ahead of a patrol as a 

lookout. 

(B) The capability of an unmanned system to perform tasks analogous to a soldier point 

man [12]. 

Prognostic Health Management. 

System using artificial intelligence or other intelligent algorithms and a combination of 

sensors and models of systems to autonomously react to environmental changes and monitor 

the operational and maintenance characteristics of the system or systems under consideration 

[16]. 

Rear Guard, Unmanned Rear Guard or Robotic Rear Guard. 

(A) The rearmost elements of an advancing or a withdrawing force. It has the following 

functions: to protect the rear of a column from hostile forces; during the withdrawal, to 

delay the enemy; during the advance, to keep supply routes open. 

(B) Security detachment that a moving ground force details to the rear to keep it informed 

and covered. {13} 

(C) The capability of a UMS to perform tasks within a detachment normally assigned to a 

human rear guard. 

Remote Control. See under Mode of Operation. 

Remotely Guided. 

An unmanned system requiring continuous input for mission performance is considered 

remotely guided. The control input may originate from any source outside of the unmanned 

system itself. This mode includes remote control and teleoperation. 

Robot/Robotic. 

An electro-mechanical system that can react to sensory input and carry out predetermined 

missions. A robot is typically equipped with one or more tools or certain capabilities, 
18 

including knowledge so that it can perform desired functions and/or react to different 

situations that it may encounter [4]. 

Robotic Follower or Leader Follower. 

The capability of a UGV to traverse a safe and tactically relevant route previously traversed <7>. 

The follower vehicle traverses the route automatically (i.e., under computer control using onboard 

sensors) potentially with significant physical or temporal separation from the leader. This 

capability takes advantage of human sensing and reasoning in the lead vehicle to reduce the 

perception and intelligence requirements for the follower vehicle. The follower vehicle may 

incorporate some limited perceptual capabilities to detect and avoid new obstacles that appear 

after the lead vehicle has passed {10}. 

Self-Healing. 

Automated or semi-automated capability of system repair, covering the infrastructure, 

hardware, and software aspects [17]. 

Self-Diagnosis. 

Ability to adequately take measurement information from sensors, validate the data, and 

communicate the processes and results to other intelligent devices {18}. 

Scout. 

Also referred to as unmanned scout or robotic scout: 

1. A person, aircraft, or ship sent out to obtain information, esp. in preparation for military 

action {13}. 

2. The capability of an unmanned system to perform tasks analogous to a human scout. 

Semi-Autonomous. See under Mode of Operation.

Sensor. 

Equipment that detects, measures, and/or records physical phenomena, and indicates objects 

and activities by means of energy or particles emitted, reflected, or modified by the objects 

and activities. [19, 20] 

Sensor Fusion: 

(A) same as fusion except limiting data source to sensors. 

(B) A process in which data, generated by multiple sensory sources, is correlated to create 

information and knowledge. Sensor information, when fused, may yield immediately 

actionable combat information and/or intelligence. The capabilities are of four essential 

types: Detection, Classification, Recognition, and Identification [9]. 

Sensory Processing. 

Computing processes that operate on either direct sensor signals or on low level sensory 

signatures to detect, measure, and classify entities and events and derive useful information, 

at proper resolutions and at levels of abstractions, about the world. Sensory processes can be 
19 

organized hierarchically with proper relative spatial and temporal resolutions and organized 

horizontally with assigned but coordinated focuses [3]. 

There are several ways to organize the progressive sensory processes, to perceive the 

resulting information, and to structure the knowledge and intelligence: 

• Levels of Fusion. See Fusion Levels. 

• Levels of Perception. See Perception Levels. 

• Levels of Cognizance. See Cognizance Levels. 

Situational Awareness. 

The perception of elements in the environment within a volume of time and space, the 

comprehension of their meaning, and the projection of their status in the future. In generic 

terms the three levels of situational awareness are level 1, perception, level 2, 

comprehension, and level 3, projection. There is both individual and group or team 

situational awareness [25]. 

Summary Model for Autonomy Levels. See under Autonomy. 

Tactical Behavior. 

A behavior that has some high level tactical significance. 

Task. 

A named activity performed to achieve or maintain a goal. Mission plans are typically 

represented with tasks. Task performance may, further, result in subtasking. Tasks may be 

assigned to operational units via task commands [3]. 

Task Decomposition. 

A method for analyzing missions and tasks and decomposing them into hierarchical subtask 

structures according to the criteria of command/authority chain, control stability, 

computational efficiency, and management effectiveness [3]. 

Teaming. 

(A) The linking together of platforms, forces, or systems to complete a mission or task

collectively that would be more difficult to do if the units acted separately. The process 

is characterized by distributed operations and high tempo maneuvers, which demands 

rapid synchronization, swift adaptation of plans and control measures, flexible groupings 

of distributed staff elements, and direct exchanges between commanders across 

hierarchies. For example, manned and unmanned platforms can be teamed to emphasize 

their complementary strengths. The unmanned systems have the further requirements of 

being able to easily and quickly communicate their intentions, goals, present state in the 

accomplishment of these goals, intended next action, and current problem areas. 

Additionally, they have to be able to be re-tasked easily to participate in the current 

overall goal and to fit into their new position in the organizational structure. The above 

is critical if they are to perform effectively in team activities [22]. 
20 

(B) A method of operation where a system uses the combined sensing, information exchange, 

decision-making, and acting capabilities of humans and robots function together to carry 

out missions within the planned scope. 

In the situations of manned – unmanned Teaming, air-to-ground teaming means that the 

manned system is in the air with UMS on the ground. Similarly, there could be air-to-air, 

ground-to-ground, and ground-to-air types of teaming. 

Teleoperation. See under Mode of Operation. 

Telepresence. 

The capability of a UMS to provide the human operator with some amount of sensory 

feedback similar to that which the operator would receive if he were in the vehicle {2}. 

Team of Teams or System of Systems. 

Grouping(s) of vehicle teams (unmanned and/or manned) for a particular mission where a 

team is a collection of vehicles for a particular task or subtask. 

Terrain. 

The physical features of the ground surface, to include the subsurface. These physical 

features include both natural (e.g., hills) and manmade (e.g., pipelines) features. Major terrain 

types are delineated based upon local relief, or changes in elevation, and include: flat to 

rolling, hilly and mountainous. Other important characteristics used to describe the terrain 

include: hydrologic features (e.g., swamps), vegetation characteristics (e.g., forests) and 

cultural features (e.g., cities). Complex terrain includes any characteristics or combination of 

characteristics that make military action difficult. Mobility classes are also used to describe 

the trafficability of the terrain. The terrain should also be rated as to its trafficability by class 

of vehicle, this is especially relevant to the use of different classes of UGVs. The three 

mobility classes are: unrestricted, restricted, and severely restricted. Derived from [26] 

Terrain Visualization. 

A component of battlefield visualization that provides a detailed understanding of the 

background upon which enemy and friendly forces and actions are displayed. Terrain 

visualization provides common terrain background for all users and all applications. 

Additionally, terrain visualization allows interactive planning and mission rehearsal. Terrain 

visualization includes both natural and man-made features to include impacts of terrain on 

vehicle speed, maintenance, river-crossing operations, cross-country trafficability, and 

maneuverability. Terrain visualization includes the subordinate elements of data acquisition, 

analysis, database management, display and dissemination. Derived from [27] 

Tether. 

A physical communications cable or medium that provides connectivity between an 

unmanned system and its controlling element that restricts the range of operation to the 

length of the physical medium [2]. 
21 

Threat Avoidance. 

Ability to detect/degrade/defeat threats. The continual process of compiling and examining 

all available information concerning threats in order to avoid encounter <5>. 

Threat Levels. 

The relative ability of an enemy, or potential enemy, to limit, neutralize, or destroy the 

effectiveness of the current or projected mission, organization, or equipment. 

Unattended System. 

Any manned/unmanned, mobile/stationary, or active/passive system, with or without power 

that is designed to not be watched, or lacks accompaniment by a guard, escort, or caretaker. 

Unmanned System (UMS). 

A electro-mechanical system, with no human operator aboard, that is able to exert its power 

to perform designed missions. May be mobile or stationary. Includes categories of 

unmanned ground vehicles (UGV), unmanned aerial vehicles (UAV), unmanned underwater 

vehicles (UUV), unmanned surface vehicles (USV), unattended munitions (UM), and 

unattended ground sensors (UGS). Missiles, rockets, and their submunitions, and artillery are 

not considered unmanned systems {2}. See the DOMAIN SPECIFIC TERMS OR 

EXTENSIONS section for extensions.

Waypoint. 

An intermediate location through which a UMS must pass, within a given tolerance, en route 

to a given goal location {2}. 

Wingman, or Unmanned Wingman, Robotic Wingman. 

(A) An aviator subordinate to and in support of the designated section leader; also, the 

aircraft flown in this role {13}. 

(B) The wingman concept assists the leader in the command and control of the system. 

During operations, the wingman orients his UMS on the section leader and, in the 

absence of orders, moves, stops, and shoots when his leader does. Anytime the wingman 

of a section is engaged or begins an engagement, the section leader supports the 

wingman’s effort {23}. 

(C) The capability of an unmanned system to perform tasks analogous to the wingman tasks 

performed by a serviceman operating a military aircraft or ground vehicle as part of a 

team or unit {24}. 

World Model. 

A UMS’s internal representation of the world. The world model may include models of 

portions of the environment, as well as models of objects and agents, and a system model that 

includes the intelligent unmanned system itself. {3}. 

Associated term: 

World Modeling. The process of constructing and maintaining a world model.
22 

DOMAIN SPECIFIC TERMS OR EXTENSIONS

Avenge Kill. 

A lethal retaliatory response to the enemy platform that has targeted or engaged friendly 

forces. This ensures destruction of the enemy that targeted our forces and discourages other 

enemy forces from sighting, targeting, or designating our forces. When a friendly 

soldier/platform is designated, the targeted platform immediately alerts supporting forces via 

the COP. The platform also deploys survivability means like obscuration/screening smoke 

and fires back to disrupt the enemy designation and engage enemy munitions fired at him. 

The targeted friendly platform fires back at the enemy as do supporting weapons systems to 

ensure the enemy is destroyed. This has the potential to psychologically affect other enemy 

attacks as they realize even by designating a UA element, they may be destroyed. The 

retaliatory fires can be executed by the targeted/engaged platform, or a supporting platform.

{25}. 

Cooperative Engagement. 

A method of engagement for destroying enemy forces, employing sensors and shooters not 

resident on the same platform [25]. 

Point and Shoot. 

A subset of cooperative engagement that allows a soldier or platform to designate a target 

for lethal engagement by another platform. The information is immediately displayed on the 

COP. Point and Shoot implies the immediacy of effects and generally occurs within the same 

echelon. 

Sensor to Shooter. 

(A) The information link from a target acquisition capability to the weapons platform(s) that 

engage(s) the target [19]. 

(B) Movement of appropriately formatted information from the reconnaissance platform to 

the attacking weapon system [21]. 

Standoff. 

Detection or lethality efforts intended to suppress an enemy threat from a position outside the 

range of the enemy threat. 

Unattended ground sensors (UGS). 

Small, low cost, robust sensors, capable of operating in the field for extended periods of time 

(30 days or more). They will consist of modular groups of sensors utilizing tailorable ground 

sensing technologies, such as seismic, magnetic, infrared, acoustic, radio frequency, and 

CBRN detection, and other advanced sensing capabilities. UGSs self-organize into a 

networked sensor array (sensor web) by locating the most efficient gateways for transmission 

of information. They are also self-healing, able to quickly bypass a neutralized gateway and 

locate a functional one within the sensor web. [Derived from conceptual work in TRADOC 

Pam 525-3-90, Maneuver O&O] 
23 

APPENDIX A. TO-DO LIST 

1. It should be considered whether external intervention other than HRI should be included in 

the definition of autonomous. If so, then, in the case of an unmanned commanding structure, 

the commander and subordinates are constantly interacting via commands and status, i.e., 

they are cooperating or collaborating. Are we saying that the entire system is fully 

autonomous, but the individual vehicles are not, and, that cooperating or collaborating are 

considered non-autonomous? 

HRI has been identified as one of the axes contributing to levels of autonomy. Does this 

imply an expansion and call “Intervention” as an axis, or do we add another axis and keep 

HRI as one on its own, due to the vast amount of research results in the subject? 

Further thoughts are needed in the next version. 

2. Another school of thoughts argues that, relatively, coordination indicates a low level of 

interaction--inform and don't conflict. Cooperation requires, in addition, for the UMSs to 

work toward a common goal. Collaboration requires the most, implying some high level, 

intellectual effort in interactions. In other words, Cooperation may occur at task level and 

Collaboration at the mission level. However, the majority of the comments within the group 

favor not distinguishing Cooperation and Collaboration.

3. Other forums (FORA? FIPA?) have looked at other class criteria, loosely based on how much 

damage they could do if they run amok (such as kinetic energy for UAVs). It depends on the 

purposes of the class definitions (the aforementioned one for safety concerns). 

4. Should reduce the UGV flavor. 

5. There is a question on whether obstacle ?= threat. A thought is that, when an entity poses 

threat, it becomes an obstacle. 

6. Subdivisions of Semi-Autonomous – By Exception and Semi-Autonomous – By 

Permission were proposed. While there might have been too much detail in terms of 

categorizing modes of control, these could be very useful in categorizing HRI effects on the 

autonomy levels. 

7. The current implementations focus on the soldier, as opposed to another UMS, to be the lead 

to provide the intelligence to develop the safe and tactically relevant path for the UMS to 

follow. This reduces the sensing, processing, and reasoning requirements for the unmanned 

follower vehicle. Since a soldier has developed the path, it should be valid. The only 

obstacles that the UMS are susceptible to are those that appear after the lead vehicle has 

passed, in which case the follower vehicle has some limited obstacle detection and avoidance 

capabilities. The key is to have the follower traverse the exact same path (within a very small 

lateral deviation) as the lead vehicle. 

As an example, consider open and rolling terrain with tall grass and some trees. A manned 

vehicle is able to maneuver through the terrain relatively easily at tactical cross-country 

speeds. A UMS without a path sees the tall grass and tress as obstacles. It can be traversed, 

but at a much slower speed than a manned vehicle because it cannot easily determine that this 

is a type of obstacle it can drive through. But now given the proven path of the lead vehicle 

and other information (such as speed), the UMS has confidence that the terrain is traversable 
24 

and can exploit that fact to increase its speed. This is the whole idea behind the robotic 

follower, using human intelligence to provide a safe path to increase performance. 

8. Should review and possibly include the terms used in the 10 levels in the Army Science 

Board Ad Hoc Study. 

9. Does autonomy require mobility? 

10. The following definitions require additional efforts: 

Levels of Control (UAV/ Unmanned Systems). FCS UAV control systems will be 

compliant with the Tactical Control System (TCS) ORD which defines five levels 

of UAV control: 

(a) Level One is the indirect receipt and direct retransmission of imagery and/or data. 

(b) Level Two is the receipt of imagery and/or data directly from the UAV and the 

functionality of previous level. 

(c) Level Three is the control of the UAV payload and the functionality of previous levels. 

(d) Level Four is control of the UAV, less takeoff and landing, and the functionality of 

previous levels. 

(e) Level Five is the full functionality and control of the UAV from takeoff to landing. 

The issues include: 

(1) Levels one and two do not speak to control at all, but simply to the receipt of data from a 

UMS. 

(2) The consensus obtained from Workshop #3 is for Control to be defined along the line of 

human authority and permission. 

(3) Control Levels are also widely used in hierarchical control theories and architectures, 

such as 4D/RCS, to define or specify commanding or authority levels in control systems. 

This concept is consistent with the aforementioned Workshop #3 consensus. 

(4) Whether and how these levels would be related to the autonomy levels. 

11. Need to clarify the following issues: 

(1) More specific terms could be used to enhance the term “greater meaning” in Fusion 

Levels.

(2) Is “a safe and tactical relevant route” required in Robotic Follower? 

12. Need to investigate the following terms for their definitions, contexts, and whether to include 

them and in which sections: 

Common Operational Picture (COP). 

A single identical display of relevant information shared by more than one command; to 

facilitate collaborative planning and situational awareness. 

Common Relative Operational Picture. 

Also investigate whether to formally define the metrics that are being developed for the three 

axes of the autonomy level framework.
25 

APPENDIX B: ACRONYMS 

4D/RCS 

NIST 4D/Real-time Control 

System Reference Model 

Architecture 

http://www.isd.mel.nist.gov/projects/rcs/ 

AATD Aviation Applied Technology 

Directorate, U.S. Army 

ACL Autonomous Control Levels 

AFRL Air Force Research Laboratory http://www.afrl.af.mil/ 

ALFUS Autonomy Levels for 

Unmanned Systems 

AMRDEC 

(Army) Aviation and Missile 

Research, Development and 

Engineering Center 

http://www.redstone.army.mil/amrdec/ 

ARL Army Research Laboratory http://www.arl.mil/main/Main/default.cfm 

ATD Advanced Technology 

Demonstrator

ATR Automatic Target Recognition 

BG Behavior Generation http://www.isd.mel.nist.gov/projects/rcs/ 

C3 Command, Control, and 

Communications 

C4ISR 

Command, Control, 

Communications, Computers, 

Intelligence, Surveillance, and 

Reconnaissance 

http://www.fas.org/irp/doddir/dod/c4isr/es.htm 

CAT Crew integration & Automation 

Testbed 

http://www.tacom.army.mil/tardec/ 

COP Common Operational Picture 

CROP Common Relative Operational 

Picture 

DARPA Defense Advanced Research 

Projects Agency 

http://www.darpa.mil/ 

DCD (Army) Directorate for Combat 

Development 

DoC Department of Commerce 

DoD Department of Defense 

DoE Department of Energy 
26 

DoT Department of Transportation 

EmCon Emission Condition 

EOB Electronic Order of Battle 

EOD Explosive Ordnance Disposal 

FCS Future Combat Systems http://www.boeing.com/fcs 

FHWA (DOT) Federal Highway 

Administration 

FM Field Manual (US Army) 

FOUO For official use only 

FWV Fixed Wing Vehicle 

HCI Human-Computer Interface 

HMI Human-Machine Interface 

HMMWV High Mobility Multipurpose 

Wheeled Vehicle 

HRI Human-Robot 

Interface/Interaction 

h hour 

INEEL Idaho National Engineering and 

Environmental Lab 

http://www.inel.gov/ 

ISD NIST Intelligent Systems 

Division 

http://www.isd.mel.nist.gov/ 

IPT Integrated Product Team 

JAUS Joint Architecture for 

Unmanned Systems 

http://www.jauswg.org 

LSI Lead Systems Integrator http://www.boeing.com/fcs 

JPO Joint Project Office http://www.redstone.army.mil/ugvsjpo/ 

JRP Joint Robotics Program 

JTA Joint Technical Architecture http://www-jta.itsi.disa.mil/ 

JTA-A Joint Technical Architecture - 

Army 

LADAR Laser Radar 

m meter http://physics.nist.gov/cuu/Units/ 

METT-TC Mission, enemy, terrain, time - 

troops, civilians 

ms millisecond 

min minute 
27 

NBC Nuclear, Biological, and 

Chemical 

NIST National Institute of Standards 

and Technology 

http://www.nist.gov/ 

NLOS Non-Line of Sight 

NRL Naval Research Laboratory http://www.nrl.navy.mil/ 

OODA Observation, Orientation, 

Decision, Action 

ORD Operational Requirement 

Document 

OSD The Office of the Secretary of 

Defense 

ROE Rules of Engagement 

RSTA Reconnaissance, Surveillance, 

and Target Acquisition 

PCD Procurement Control Drawing, 

(essentially a specification) 

RDECOM 

(Army) Research,

Development, and Engineering 

Command 

s second 

SA Situational Awareness 

SI International System of Units http://physics.nist.gov/cuu/Units/ 

SoS System of Systems

SP Sensory Processing http://www.isd.mel.nist.gov/projects/rcs/ 

SED Software Engineering 

Directorate 

http://www.redstone.army.mil/amrdec/directorates/

sed/index.htm#main 

TACOM U.S. Army Tank-Automotive 

and Armaments Command 

http://www.tacom.army.mil/ 

TARDEC 

Tank Automotive Research, 

Development and Engineering 

Center 

http://www.tacom.army.mil/tardec/ 

TCS Tactical Control System 

TTP Tactics, Techniques and 

Procedures. 

UAMBL Unit of Action Maneuver 

Battlelab 

UARV Unmanned Armed 

Reconnaissance Vehicle 
28 

UAV Unmanned Aerial Vehicle 

UCAR Unmanned Combat Armed 

Rotorcraft 

http://www.boeing.com/defensespace/military/unmanned/ucar.html 

UGS Unattended Ground Sensors 

UCAV Unmanned Combat Air Vehicle http://www.darpa.mil/ucav/index.htm

UGV Unmanned Ground Vehicle 

UML Unified Modeling Language 

UMS Unmanned System 

USV Unmanned Surface Vehicles 

UUV Unmanned Undersea Vehicles http://www.onr.navy.mil/fncs/auto_ops/default.asp 

UVA Unmanned Vehicle Architecture 

UXO Unexploded Ordnance 

VJ Value Judgment http://www.isd.mel.nist.gov/projects/rcs/ 

VRA Vehicle Electronics (Vetronics) 

Reference Architecture 

WM World modeling http://www.isd.mel.nist.gov/projects/rcs/ 

WSTAWG Weapon System Technical 

Architecture Working Group 

http://wstawg.army.mil/ 

XUV eXperimental Unmanned 

Vehicles 
29 

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30 

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