Small Wars Journal

Medical Robotic and Autonomous System Technology Enablers for the Multi-Domain Battle 2030-2050

Sat, 07/22/2017 - 6:32pm

Medical Robotic and Autonomous System Technology Enablers for the Multi-Domain Battle 2030-2050

Nathan T. Fisher and Gary R. Gilbert


Future combat strategies such as the Army’s Multi-Domain Battle concept will likely involve greater dispersion, near isolation, and area denial challenges necessitating units to be more logistically self-sufficient. This is likely to result in severe mobility restrictions for medical missions and shortfalls in both human and materiel resources. The numbers of manned evacuation platforms are likely to be insufficient for wide-spread multi-domain battlefields with peer/near-peer adversaries or Anti-Access/Area Denial (A2AD) environments. Without new combat casualty care and force multiplication strategies, combatant commanders with mounting sick or wounded will face degraded medical resources and encumbered combat mobility.

The Army’s Robotic and Autonomous Systems Strategy (RAS) [1] involves leveraging robotics and autonomous systems to penetrate high-risk areas and to provide support in contested environments to increase reach, capacity, and protection. Unmanned Aerial Systems (UAS) and Unmanned Ground Vehicles (UGV) will be staged forward with support units providing multi- functional utility for many mission sets. Unmanned Systems (UMS) have the potential to assist in the timely delivery of critical medical supplies in support of prolonged field care when evacuation is not possible and to assist in expedited casualty evacuation when conventional manned assets are not available. A general purpose UMS which can be configured to support casualty evacuation would provide a key secondary utility and vehicle of opportunity as a medical mission enabler. The maneuver Commander, who is ultimately responsible for clearing wounded from the battle space [2], could leverage this capability to effectively increase the overall mobility of both medical and non-medical units in future operational environments.

However, reliable closed-loop intervention [2,3] is yet an unsolved Artificial Intelligence challenge; without which adequate enroute care would be sacrificed during casualty evacuation on UMS without medical oversight. Accordingly, in 2019 the US Army Medical Research and Materiel Command (USAMRMC) will begin funding long-term research in: 1) Medical Robotics aimed at the use of robotics to support medical tasks such as tele-robotic surgery and robotic enroute care during patient extraction from contested or denied areas; 2) Autonomous and Unmanned Medical Capabilities aimed at automated patient monitoring and closed-loop interventions to enhance patient hold capabilities at NATO Roles 1-3 and leveraging emerging general purpose UMS platforms for medical missions such as autonomous ground and air patient evacuation and delivery of emergency medical supplies; and 3) Medical Aspects of Manned-Unmanned Teaming (MUM-T) which will develop medical performance criteria to ensure Warfighters have the physical, cognitive, and psychological capacity to effectively team with robotics and autonomous systems.


In 2009 we contributed to the US Army Training and Doctrine Command (TRADOC) assessment of the state of medical robotics and their potential application to combat casualty care [4]. While only a few of the TRADOC documented “Warfighter Outcomes” involved robotics for medical and surgical tasks, topics suggested for improvements in the areas of field medical care and force health protection through robotics included faster casualty recovery and evacuation by fewer personnel, faster and more certain recognition of injuries, and enhanced forward care through remote tele-robotic capabilities. Following is what we considered at that time to be the current state and future potential for the combat casualty care robotic applications as suggested in TRADOC’s paper:

Perform Battlefield First Aid. Self-assistance by the soldier or the availability of buddy care cannot be assumed in all combat situations; likewise, there are never enough combat medics or combat life savers to treat and extract all casualties, especially during intense close combat or  in contaminated or otherwise hostile environments. The Army Institute for Soldier Nanotechnology at MIT has conducted basic research in uniform-based diagnostics and emergency injections and sewn-in tourniquet loops on uniforms are under consideration. Slow progress is being made in development of sophisticated sensors, autonomous analysis of sensory input, and autonomous application of intervention and treatment procedures, but deployment of such robots is years away.

Recover Battlefield Casualties. As with battlefield first aid, universal availability of combat medics or other soldiers assigned to perform extraction and recovery of casualties cannot be assumed. Therefore, a means to autonomously find, assess, stabilize, and then extract casualties, especially under fire or in otherwise hostile environments, for further evacuation is needed. This may be complicated by unknown nature of injuries, which may complicate or confound rote mechanical means of body movement; a compound fracture or severed limb might not be gripped, or gripping may increase injury.  Previous research has addressed the potential complications of robotic casualty extraction [5,6,7]. The tele-operated semi- autonomous Battlefield Extraction Assist Robot (BEAR) represented a prototype casualty extraction capability which was intended to carry a 500 pound load while traversing rough and urban terrain with dismounted soldiers.  A fully autonomous version of the BEAR would need significant artificial intelligence programming and a transparent hands-free soldier-robot interface to execute this mission in combat while keeping the soldier-operator focused on their primary mission. Research in autonomous flight control and navigation technologies needed for casualty evacuation on UAS continues [5,6,7,8] but actual employment of operational systems is probably years away because of the immaturity of autonomous enroute casualty care systems.

Robotic Detection, and Identification of Force Health Protection Threats. Detection and identification of chemical and biological threats to which combat casualty patients may have been exposed, and segregation and containment of contaminated casualties prior to receiving casualties in forward medical and surgical treatment facilities are critical capability needs. Several research projects were conducted in robotic detection and identification of chemical and biological and agents and chemical contaminants [6,7]; they utilized robotic enabled photonics as well as antigen-based detection technologies. The goal was to produce modular threat detection and identification systems that can be implemented on robots performing missions like casualty extraction.

Perform Tele-robotic Surgery. At first glance, remote tele-robotic surgery capability appears to already exist since minimally invasive operations have been remotely performed using dedicated fiber optic networks; daVinci surgical robots have been and are currently used in both military and civilian hospitals and many other tele-robotic surgery demonstrations have been conducted around the world [5]. Nevertheless, while significant research has been conducted in physiological sensor and image-based robotic casualty assessment and triage [5,6,7], visual examination information is planar, and may lack depth and full 5-sense information (e.g., tactile feedback).  The DARPA ‘Trauma Pod’ project was an attempt to leverage advanced imaging technologies and robotics to enable autonomous casualty scan, diagnosis and intervention. Military funded research has demonstrated that surgical robotic systems can be successfully deployed to extreme environments and wirelessly operated via microwave and satellite platforms. However employment of these capabilities on the battlefield have not yet progressed beyond experimental proofs of concept, are not ruggedized, and are tele-operated component capabilities at best. Significant additional research is  required to develop supervisory controlled autonomous robots that can overcome the operational communication challenges of limited bandwidth, latency, and loss of signal in the deployed combat environment. Addressing acute and life threatening injuries such as major non-compressible vascular injury requires development of new surgical robots that move beyond stereoscopic, bimanual tele-manipulators and leverage advances such as autonomous imaging analysis and application of directed energy technologies already used in non-medical military robotic systems.

New Army Medical Science & Technology Research Areas in Robotics, Autonomous, and Unmanned Systems

The growth of robotics, autonomous, and unmanned systems and associated enabling technologies on the future battlefield affords both great opportunities and challenges to far future medical operations in the Multi-Domain Battlespace. Robotic, autonomous or near autonomous patient support systems integrated with general purpose unmanned platforms systems could serve as force multipliers for medical operations in future environments especially in enabling expedited casualty evacuation. The proposed new Army medical S&T research areas cited above and described below will enable initiation of a multi-year research program leading to prototyping efforts in these areas of research:

Medical Robotics. As robotic capabilities continue to evolve, autonomous and tele-operated semi-autonomous robotic patient support systems could enable closed-loop patient monitoring and triage as well as robotic intervention. In addition to what may be considered as contemporary robotics, i.e. an integration of knowledge-based software with electrical and mechanical engineering technologies, or so-called “hard robotics”, one approach to employing robotics for medical applications is the emerging field of so-called “soft robotics”. While future deployment of hard robotics may enable the Army to deliver immediate damage control surgery and interventions at the point of injury and improve the ability to deal with mass casualty scenarios, there has also been an increasing interest in the use of soft and deformable structures in the robotic systems to reduce combat loads. The proposed Army Science and Technology Medical Robotics research areas will enable us to initiate research leading to prototyping efforts in: 1) soft robotic-driven imaging and critical care intervention technologies that can enable closed-loop resuscitation and guide critical care interventions in future arrays of ruggedized and lightweight autonomous care systems to support prolonged field care as well as enroute care during casualty evacuation in unmanned systems. 2) Identification and mitigation of problems caused by signal latency that hamper tele-robotic surgery, thereby enabling safe and effective tele-robotic surgery that supports critical care forward on the battlefield.

Autonomous and Unmanned Medical Capability. This research area will investigate approaches to automating diagnostics and therapeutics in the field and research feasibility for integrating those capabilities on UMS platforms to enable patient evacuation as well as just-in-time medical resupply missions. Research will include 1) intelligent agent approaches to closed-loop system- of-systems algorithms incorporating use of multiple autonomous critical care systems during prolonged field care or extended evacuation with focus on new approaches to autonomous clustering and intelligent agent algorithms that interact with each other to enable development of autonomous closed-loop systems care for multiple injuries (multi-trauma) while deconflicting the various autonomous procedures, 2) strategies for interfacing closed-loop diagnostic and critical care systems with autonomous unmanned ground and air platforms to allow for expedited care of combat casualties and extended evacuations on UMS, and 3) research in the area of artificial intelligence and perception systems for accurate detection and modeling of the human body to enable semi-autonomous casualty extraction and closed-loop enroute care systems; these applications require high fidelity mapping of the human body in near-real time for safe physical contact with the casualty, or more generally, when operating in close proximity to Soldiers.

Enabling Technologies

Mission-based Intelligent Flight Controllers

Using non-dedicated UMS for casualty evacuation presents significant challenges in terms of patient safety and continuity of medical care and should be used only under careful consideration. Important safety considerations were documented by a NATO Task Group which investigated the possibility and acceptability of UAS casualty evacuation [9]. Without a human onboard, unmanned vehicles are only bound by their physical design limitations and are capable of operating outside of human safety limits. There are three general approaches to limiting patient exposure to harmful effects induced by the vehicle or the environment during transport: 1) vehicle design, 2) flight characteristics controlled by the flight control systems, and 3) patient restraint systems and other medical equipment. All three approaches are likely needed in varying degrees to ensure patient safety concerns are appropriately addressed during unmanned patient transport.

Importantly, patient safety concerns must be addressed without imposing onerous functional requirements on the design of the UAS platforms that may hinder performance in primary roles. One method that will help achieve this goal is to implement an intelligent flight control systems capable of adjusting critical flight parameters based on mission constraints to ensure safety thresholds are not exceeded when operating in casualty evacuation mode. This capability would ensure safe patient transport onboard UMS by directly interfacing with the vehicle’s controller to modify the vehicles ride profile to avoid exposing the casualty to potentially harmful acceleration or environmental effects during transit. A pre-defined set of mission-based constraints could be further refined by catering the vehicle’s ride profile based on the patient’s injury type.  For example, if the patient is at risk of hypoxia (deficiency in the amount of oxygen reaching the tissues) and there is no supplemental oxygen system available, altitude restrictions may be required.

Methods for interfacing with the field medic during casualty evacuation missions are needed   for the mission-adaptable intelligent flight controller to effectively understand the patient’s condition and modify the vehicle’s behavior accordingly. For example, the medic’s Nett Warrior device, which may be used to capture the medical encounter data electronically [10], could interface directly with the vehicles flight controller to communicate the patient’s conditions that affect route planning and relevant flight parameters. Research is required to better understand the relationship between exposure during transport and patient outcomes. Once defined, exposure thresholds by injury type can then be mapped to the vehicles operating parameters through engineering design and development. Adapting on-the-fly to mission- based constraints is not only useful in adapting UMS for medical missions, but is generally required for UMS to have the flexibility to fill multi-functional roles in the future battlefield.

Integration of Medical Systems with General Purpose Unmanned Vehicles

Further integration of medical systems and unmanned vehicles could provide additional  medical capabilities when unmanned vehicles are used for expedited casualty evacuation. If medical information systems, like patient monitors and telemedicine devices, were integrated with unmanned vehicle platforms, the native tactical radios onboard could be used for medical data exchange. It is likely that the only means available for transmitting medical data while enroute onboard multipurpose unmanned vehicles is through integration with the vehicles existing command and control infrastructure. Transmission of medical data during transit is an important enabler for a wide range of current and future medical technologies for enroute care [10]. For example, integration with the unmanned vehicles radio network can allow medical encounter data captured in the field and live patient vitals data to reach the receiving medical treatment facility while enroute. This allows the receiving medical care provider to closely monitor the casualty remotely and review the patient’s injury assessment and prior treatment through transmission of the patient’s medical records ensuring seamless medical data exchange throughout the continuum of care from the point of injury through arrival at the medical treatment facility. One approach that has been successfully demonstrated in past field exercises is the integration of telemedicine data with the vehicle’s communication system by leveraging an existing open architecture developed for interoperability between disparate unmanned vehicle platforms, called the Unmanned Systems Control Segment (UCS) [11]. UCS was extended to include a telemedicine domain to facilitate future integration of medical devices and information systems with unmanned vehicles so that they may be utilized as needed to support medical operations.

Further development and promotion of methods for achieving interoperability between different unmanned platforms is foundational to the MUM-T concept which is a core component of the Third Offset Strategy and Multi-Domain Battle [12]. Because of the strategic emphasis on MUM-T, the Army is developing a Scalable Control Interface (SCI) to control future UAS using a common software framework that is scalable to different form factors (e.g. field operator’s hand-held or static ground control stations) [13]. UCS and SCI are two examples of interoperability frameworks that could be extended to facilitate integration of medical systems with future unmanned vehicle platforms. Medical integration with UMS will be increasingly important as patient management systems become more portable and capable. Automation of certain critical care functions utilizing closed-loop control systems based on algorithms using input from patient monitors is a focus area of current research [14]. These technologies could be incorporated into remote-controlled/supervised patient management systems capable of semi-autonomous control of functions like mechanical ventilation management, blood infusion, and drug delivery. Integration of medical capabilities with emerging unmanned vehicles requires active development to ensure that the proper interfaces are defined between the vehicle and the medical device. Interoperability standards are critical in designing medical interfaces to UMS because they must be compatible with multiple UMS platforms as a rapid roll-on/roll-off capability for hasty casualty evacuation.

Multi-robot Teams and Swarms

Research and development in technologies to enable multi-robot teams to work collaboratively to meet mission objectives is an active area of research in the Army and across the DoD [15].

There are significant advantages in using teams of smaller robots to execute complex tasks that would otherwise be very difficult for any individual robotic platform. DARPA has been developing robot swarming capabilities for both ground and air UMS where a large number of UMS come together upon command, or as result of semi-autonomous or autonomous mission analysis, to achieve a common objective [16,17]. Because these teams of robots are able to disperse and coordinate efforts, they are able to conduct certain operations with much more speed and agility. These small common-use swarm robots also can be designed to be affordable and expendable. Emerging robotic teaming and swarming technologies can be leveraged to provide standoff medical capabilities that would not otherwise be available. For example, an individual robotic platform is unlikely to be able to perform all the required tasks for a semi-autonomous casualty extraction mission. However, a team of small mobile robots could team up to collaboratively perform the required tasks of locating, assessing, and  extracting a casualty in a high-threat environment without risking additional lives, with a human in the loop for supervision and high-level commands.

Small UAS (sUAS) have the ability to compliment other types of systems, both robotic and conventional, during medical operations due to their increased speed and agility. For example, medical operations that require a mobile ground robot could benefit from teaming with a sUAS to provide a bird’s-eye view for real-time terrain mapping and environment assessment to assist the ground robot in navigation and mission planning. Similarly, sUAS can team with larger aircraft, both manned and unmanned, for casualty evacuation applications in congested/dense urban environments as intelligence, surveillance, and reconnaissance (ISR) assets that can be sent ahead of the large aircraft to assist in landing zone evaluation and obstacle/threat detection in the vicinity of the planned route. There are also concepts  emerging for modular vertical lift capabilities consisting of multiple small vertical take-off and landing (VTOL) UAS to self-assemble and collaboratively lift and transport larger payloads [18]. These modular systems can easily scale up payload capacity by adding more VTOL UAS modules to the system. The individual modules have the ability to navigate independently to carry small payloads or to easily maneuver to the assembly point where collaborative lift is required for larger payloads like casualty extraction. This concept is especially compelling during operations in complex environments like dense urban areas where larger vehicles, both air and ground, are likely to experience maneuver challenges. Such flexible and modular UAS lift capabilities have future applications in providing emergency medical resupply to dispersed units operating in challenging terrain and contested environments. It is also conceivable that such systems could be used for short distance evacuation of casualties to a nearby safe zone for handoff to a MEDEVAC team.

Besides small teams of robots collaborating for medical functions, there are also potential operational medicine applications of robot swarms consisting of many individual robots such as those envisioned by the DARPA OFFensive Swarm-Enable Tactics (OFFSET) program [16]. This program seeks to develop disruptive swarm tactics to assert and maintain superiority in future urban operating environments. While this DARPA program is focused on offensive maneuvers, swarm technology has the potential to address challenges imposed by complex, dynamic, and unpredictable urban environments and is applicable to a wide range of mission sets, including medical. These robot swarms will be able to rapidly distribute sensors across sections of the battlefield without putting either soldiers or large/expensive robotic assets at risk. Medical operations could benefit from the information gained through rapid dissemination of sensors across the battlespace. Medical-specific sensors, e.g. bio-threat/CBRNE detectors, could be integrated with the swarm robots if they are able to be sufficiently miniaturized. Visual data obtained by the swarms may also be analyzed for important information for medical missions, e.g. for casualty detection, location, and remote assessment. Analyzing visual data obtained by these swarms for casualty detection and location may require more computational power than is possible using the system’s onboard hardware, however this data could be processed at a centralized server to provide this capability.

Unique Mobility Robotic Platforms for Challenging Environments

Providing standoff medical capabilities utilizing robotics and autonomous system requires platforms that are able to effectively navigate the multi-domain battlespace consisting of highly unstructured environments and complex threats. Innovative mobility solutions may be required to overcome challenging terrain and lack of persistent air superiority. Recent advancements in robotic systems include novel approaches to locomotion including the ability to transform between mobility modes to adapt to changing terrain or navigate through obstacles. These innovative technologies could provide future robotic systems with the maneuver capabilities needed to support dispersed and hard-to-reach units in the future battlefield, including medical support.

The capability for a military mobility platform to quickly transform between a ground vehicle and an air vehicle or from a utility vehicle form (e.g. truck) to human-like biped is a concept that has been explored in the past with varying degrees of success. Traversing on the ground and flying in the air each have distinct maneuver advantages, and therefore a platform that is capable of quickly transforming between different mobility modes would be advantageous.

These hybrid “transformer” vehicles are conceptually appealing to multi-domain battle strategies which rely on being able to quickly create and exploit temporary windows of advantage over the enemy. Such vehicles could adapt their mode of mobility not only based on environmental conditions and terrain but also based on changing maneuver threats in the battlespace.

An example of past efforts includes the Piasecki Air-Jeep platform which demonstrated this concept using two ducted horizontal rotors in tandem in the 1960s [19]. In more recent times, this air/ground vehicle transformer concept has been demonstrated by other companies, including Advanced Tactics “Black Knight Transformer” platform [20]. When compared to the performance of conventional air and ground vehicles, these types of vehicles historically cannot achieve the same level of performance when operating in their respective modes. It is challenging to define “good-enough” performance in both mobility modes to justify the increased complexity required for a transformer-type vehicle.

The DARPA Transformer (TX) program started in 2009 with a similar goal, i.e. to develop a terrain-independent vehicle combining ground vehicle and VTOL capabilities. This concept evolved to include two separate detachable modules that were capable of operating independently in their respective modes and attaching to operate as a single unit when required. This is perhaps a more practical approach to the transformer concept, and also supports the concept of using the common flight module not only to move the ground vehicle module, but also other mission-specific modules. This is the concept for the current DARPA Aerial Reconfigurable Embedded Systems (ARES) program, successor of the Transform (TX) program, a VTOL UAS platform intended to support multiple detachable mission modules, including a casualty evacuation module [21].

Unique mobility platforms are also being explored for smaller robotic platforms to enable them to team with dismounted soldiers. Developing robotic platforms capable of maneuvering on the ground through the same terrain that a dismounted soldier is capable of traversing is a difficult challenge. Tracked and wheeled ground robots struggle on unstructured terrain or when faced with urban obstacles such as stairs or doors. Robots capable of traversing urban obstacles with unique mobility and manipulation capabilities were on display during the DARPA Robotics Challenge (DRC) Finals in 2015. Team KAIST’s DRC-HUBO [22] and NASA’s Jet Propulsion Laboratory’s Robo-Simian [23] are two examples of robotic platforms with unique mobility and manipulation capabilities. Both platforms have two different mobility modes, bipedal walking and wheeled locomotion in the case of the DRC-HUBO, which allow them to more effectively traverse the DRC obstacle course. While many of the DRC robots were able to complete the obstacle course successfully, they were not able to do so at anywhere near the speed of a human. Increasing the operational tempo of these robots is required for effective MUM-T in the multi-domain battle.

The mobility and manipulation capability limitations of today’s state-of-the-art ground robots make medical functions, like robotic casualty extraction, a difficult problem under even the most forgiving conditions. Robotics and autonomous systems have the potential to introduce truly disruptive technologies to the battlefield. However, to be effective in the future multi- domain battle, they must be able to operate quickly in highly dynamic and unstructured environments. Advanced systems using unique mobility and dexterous manipulators would be required to provide a casualty extraction capability for complex environments including situations in which casualties are located in multi-level buildings, subterranean environments, or under rubble, for example. A one-size-fits-all approach for a robotic system for casualty extraction is unlikely to work in all types of conditions and terrains and therefore, innovative robotic solutions using unique mobility platforms and dexterous manipulation capabilities should continue to be investigated using either a single robot or a team of robots to perform casualty extraction in challenging environments/conditions.

“Soft” Robotics

Augmented by conventional robotics technologies (i.e. electro-mechanical systems with mostly rigid elements, or “hard robotics”), the emerging field of so-called “soft robotics” [24] has many potential medical applications. Soft robotics involves the use of deformable structures to accommodate uncertain and dynamic task-environments, e.g. grasping and manipulation of unknown objects, locomotion in rough terrains, and physical contact with human bodies.

Emerging technologies broadly categorized as “soft robotics” have the potential to augment traditional robotic systems in ways that are likely to make robotic and autonomous systems more applicable to medical applications for combat casualty care in pre-hospital environments.

Perhaps the most appealing attribute of soft robotic systems for combat casualty care applications is that they are inherently safer than traditional systems because they are at least in part constructed using compliant materials that are less likely to do harm when in physical contact with a person. The compliant nature of soft robotics also lends itself well to medical applications because of the ability to more easily conform to the organic shapes of the human body to provide more uniform pressure at the human-robot physical interface. Another beneficial attribute of soft robotic systems is their potential to be miniaturized and thereby increase their applicability to medical applications in the field and during casualty evacuation where space and weight capacity is limited. However, the tradeoff for using compliant materials is that methods of achieving precise and accurate position control of the robot’s end-effector are much more complex. Moreover, investigations of soft materials are also necessary for   more visionary research topics such as self-repairing, growing, and self-replicating robots.

Despite its importance, the field of Soft Robotics faces a number of fundamental scientific challenges. The studies of unconventional materials are still in their exploration phase; it has not been fully clarified what materials are available and useful for robotic applications; tools and methods for modelling and simulation and fabrication and assembly of soft continuum bodies are not well established; it is not fully understood how to achieve sensing, actuation and control in soft bodied robots; and we are still exploring effective means of testing, evaluating, and communicating soft robotics technologies. Despite such challenges, soft robotic-driven imaging and interventional technologies to guide critical care interventions in future ruggedized and lightweight autonomous care systems has the potential to inject an increased level of medical care further forward in the multi-domain battlespace in support of prolonged field care and enroute care in unmanned systems.


The Multi-Domain Battle concept is likely to cause severe restrictions on mobility for medical missions and shortfalls in both human and materiel resources due to area denial challenges. Combatant commanders with increased sick or wounded soldiers will face degradation of medical resources and encumbered combat effectiveness without new combat casualty management and force multiplication strategies. Robotic and autonomous or semi- autonomous patient support systems integrated with general purpose unmanned vehicle platforms could serve as force multipliers for medical operations in future environments especially in enabling expedited casualty evacuation. The Army has created three new S&T research areas with potential to become significant force multipliers in support of prolonged field care, especially when early entry medical evacuation assets are denied entry or not available. The Medical Robotics research area will focus on delivery of medical care and patient handling to include automated patient monitoring and assessment functions for patient hold capabilities, aid in patient extraction from contested areas, and autonomous closed loop interventions. The Autonomous and Unmanned Systems Medical Capability research area will focus on autonomous and unmanned delivery of medical capabilities such as delivery of forward resuscitation treatment and emergency medical resupply as well as closed-loop enroute care modules that could enable general purpose unmanned vehicles to perform casualty evacuation missions. The Medical Aspects of Manned-Unmanned Teaming research area will develop medical performance criteria to ensure Soldiers have the physcal, cognitive and psychological capacity to perform in the context of manned/unmanned teaming with autonomous systems and unmanned platforms. Specific research approaches and enabling technology research areas to consider include mission-based intelligent flight controllers, integration of medical systems with general-purpose unmanned vehicles, multi-robot teams and swarms, unique mobility robotic platforms for challenging environments, and so-called “soft robotics”. While proposed research in the new Army medical S&T research areas will focus on exploration of such research approaches for both adoption and adaption to medical mission areas, the medical community has neither the resources nor expertise to develop expensive single function robotic platforms; significant attention will be given to coordinating, collaborating and leveraging RAS research in other DoD labs, academia and private industry.

Moreover, coordination of this research within the Army and across the services is vital to ensure consistency in joint medical operations, medical care and medical regulation as well as to ensure that future military RAS platforms are being designed with human systems mission- dependent constraints and those built-in capabilities required downstream to support medical missions.

The views, opinions and/or findings contained in this research are those of the author(s) and do not necessarily reflect the views of the Department of Defense and should not be construed as an official DoD/Army position, policy or decision unless so designated by other documentation.

Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the U.S. Government.


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[2] Fisher, Nathan & G.R. Gilbert, “Unmanned Systems in Support of Future Medical Operations in Dense Urban Environments”, Small Wars Journal, Feb 4, 2016. operations-in-dense-urban-environments.

[3] Berkow, John & R. Poropatich, “TRAuma Care In a Rucksack” (TRACIR), a Disruptive Technology Concept”, Small Wars Journal, Feb 19, 2016.

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About the Author(s)

Gary Gilbert leads the USAMRMC Telemedicine & Advanced Technologies Research Canter (TATRC) Medical Intelligent Systems Laboratory.  Composed of a robust group of research scientists and technologists in the fields of artificial intelligence, robotics, engineering,, computer science, telecommunications as well as experienced research managers and field operators in combat health services support and force health protection, this lab is focused on engineering the future of military operational medicine in the Multi Domain Battlespace.  After receiving advanced degrees in Agriculture, Dairy Science, and Management of Information Technology, from Cornell, Penn State and American University, Dr. Gilbert served in the U.S. Army as a Medical Service Corps Commander and Staff officer, which included service as a Special Forces Operational "A" Detachment Commander and Medical Plans, Operations, and Training Officer. Also while in the Army, he received a Ph.D. in Business with specialization in Artificial Intelligence and Medical Informatics from the University of Pittsburgh. He has served as Director of Information Systems (CIO) at Walter Reed and Tripler Army Medical Centers in Washington, DC, and Honolulu, HI; CIO of the Army Medical Research and Materiel Command (MRMC) and Director of the Army's Telemedicine and Advanced Technology Research Center (TATRC) at Fort Detrick, MD. He was instrumental in developing and implementing numerous Department of Defense medical information systems, initiating a variety of military medical informatics projects, and creating the Army's telemedicine program.   In his current position he oversees numerous research projects in robotics, artificial intelligence, biomedical informatics, operational telemedicine and medical information exchange in tactical environment; this includes a portfolio of unmanned systems research projects aimed at autonomous combat casualty care and evacuation.

Nathan Fisher is a Project Manager, Mechanical Engineer, and Research Scientist working for the US Army Medical Research and Materiel Command’s (USAMRMC) Telemedicine and Advanced Technology Research Center (TATRC) since 2014. Prior to this role, Nathan worked for eight years as a Mechanical Engineer supporting the design and manufacturing of various vehicle systems, including military combat vehicles and commercial aircraft systems. Nathan’s current professional focus is in the adaptation of emerging robotics technologies to provide future capabilities for combat medics in far-forward operational environments. Nathan holds a M.S. degree in Mechanical Engineering from Johns Hopkins University and a B.S. degree in Mechanical Engineering from the University of Maryland.