Scalable, Adaptive, and Resilient Autonomy (SARA)

Objective

Future Army forces will need to conduct cross-domain maneuver (CDM) and at times, operate semi-independently, disbursed, and while communications and infrastructure such as GPS are disrupted or denied. Robotics and Autonomous Systems (RAS) will play a key role in expanding the operational reach, situational awareness, and effectiveness of maneuver forces in CDM.

The U.S. Army Combat Capabilities Development Command (DEVCOM) Army Research Laboratory (ARL) is focused on developing fundamental understanding and informing the art-of-the-possible for warfighter concepts through research to greatly improve air and ground based autonomous vehicle perception, learning, reasoning, communication, navigation, and physical capabilities to augment and increase the freedom of maneuver in complex and contested environments.

The Scalable, Adaptive, and Resilient Autonomy (SARA) program is focused on developing and experimentally accelerating emerging research in autonomous mobility and maneuverability, scalable heterogeneous and collaborative behaviors, and human agent teaming to realize adaptive and resilient Intelligent Systems that can reason about the environment, work in distributed and collaborative heterogeneous teams, and make op-tempo decisions to enable Autonomous Maneuver in complex and contested environments.

Contact Information

ARL Collaborative Alliance Manager:
Eric Spero
Office: 410-278-8743
Mobile: 240-687-7334
eric.spero.civ@mail.mil

Important Documents

Important Dates

  • Opportunity released 15 January 2019
  • Opportunity Webinar 24 January 2020
  • Deadline for Questions on Funding Opportunity 31 January 2020
  • Proposals due for Cycle 1 14 February 2020
  • Cycle 1 Awards April 2020 (Expected)

SARA Cycle 1: Information and Updates: The SARA program will consist of a series of technology sprint topics executed in annual program cycles. Each topic will be focused on addressing a different scientific area within the scope of the broad research aims of the SARA program. Each topic will be carefully chosen based on both program achievements from the previous year, on scientific and technological advancements by the broader research community, and in a way to systematically converge on the specific long-term SARA program goals. The SARA Cycle 1 Technology Sprint Topic is “Off-Road Autonomous Maneuver.” Within “Off-Road Autonomous Maneuver,” there are three sub-topic areas of interest as described below.

Sub-topic #1: Off-road autonomous “GROUND” maneuver:  Army RAS will need to operate in environments much more complex, unstructured, and with less infrastructure than what is currently being developed for commercial applications such as driverless cars. Future Army autonomous ground systems such as the Robotic Combat Vehicle will need to traverse complex off-road environments with limited previous knowledge of the environment, human interventions, or external supporting infrastructure. In order to demonstrate the necessary robustness to unknowns and resiliency in complex environments, significant advancements in algorithms for autonomous navigation in perception, learning, reasoning, decision making, and adaptive planning will be required. Sprint sub-topic area #1 is focused on how to increase the operational tempo and mobility of autonomous ground systems to traverse increasingly complex off-road environments.

Sub-topic #2: Autonomous “AERIAL” maneuver through off-road environments: Future ground autonomous vehicles will not operate in isolation, they will be teamed with other ground robotics, small and large unmanned aerial systems, and with dismounted and mounted Soldiers.  Sub-topic area #2 begins to explore how to increase the operational tempo and mobility of aerial autonomous systems to navigate increasingly complex off-road environments such as forest roads, along field edges, and above, through, and under canopy forested environments in order to support ground platforms and dismounted Soldiers. Addressing this sub-topic area will require significant advancements in algorithms for autonomous navigation in perception, learning, reasoning, decision making, and adaptive planning to succeed. UAS may carry a diversity of computers, sensors, radios, and other payloads. Hardware designs may implement possibly well-known methods but particular consideration must be given to the low size, weight, and power requirements concomitant with small unmanned aerial systems. Sprint sub-topic area #2 is focused on how to increase the operational tempo and mobility of autonomous aerial systems to traverse increasingly complex off-road forested environments.

Sub-topic #3: Large scale heterogeneous autonomous systems experimentation: Software infrastructure to orchestrate and manage large-scale air-ground collaborative experiments. Even single agent experiments increasingly employ highly complex software systems requiring management of execution, runtime monitoring, configuration, and version-control and validation of emergency stop functionality and other safety measures. Replicating these complexities across large-scale multi-agent experiments, including concerns such as vehicle deployment and battery management, only compounds the challenge and deters reproducible experiments.

For full program opportunity details, click the Program Announcement.