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A Remote Egg-oiling System with Autonomous and Automated Target Object Identification for Nuisance Bird Management


TECHNOLOGY AREA(S): Air Platform, Sensors 

OBJECTIVE: Develop an inexpensive autonomous remote egg-oiling system that can use automated target object identification to search for and find target nuisance bird nests and eggs. The system will need to be able to self-navigate, avoid collision with a variety of unexpected objects in its path, self-search for target objects, and when the appropriate target is found, allow the operator to make the final decision as to whether to initiate oiling target eggs. 

DESCRIPTION: Nuisance birds on Department of Defense (DoD) facilities can exact heavy tolls on military operations, training, equipment (e.g., aircraft, helicopters) and personnel safety for all DoD services. In 1995, 24 crew members were killed after an Air Force jet sucked geese into its engine intake and crashed. These aircraft strikes cost the military more than $75 million per year in damage. The Navy spends millions of dollars a year to reduce Bird/Wildlife Aircraft Strike Hazards (BASH). In order to be able to conduct testing and training activities, the DoD spends over $50 million per year to manage threatened and endangered (T&E) species and satisfy DoD obligations for T&E species (Ref 1). Nuisance bird species pose significant threats to many T&E species, contributing to their decline and leading to greater expenditures and restrictions or even stoppage of military activities on DoD lands (e.g., training activities are limited to a particular season and/or certain areas). There is not a unifying characteristic of bird species that are considered nuisances and which species are deemed nuisances will vary by location and be context-dependent (e.g., birds in areas that we don't want them to be or harming species that we are trying to conserve). Effective and cost-efficient means for managing and reducing nuisance birds are crucial to diminishing bird impacts on military readiness. The most common approach for nuisance bird control is reducing the number of individuals (e.g., killing, removing, or transplanting individuals). One of the most well-established and least controversial methods to reduce local numbers of nuisance birds is applying oil (food-grade or non-toxic; see Ref 2) to eggs in the nest (Refs 3, 4). The oil prevents oxygen exchange across the egg shell, causing developing embryos to die, but parents continue incubating the eggs and do not re-nest (Ref 5), thus, reducing reproduction. Currently, egg-oiling is restricted to easily accessible nests due to safety concerns for personnel and to avoid areas with potentially sensitive equipment. NAVFAC Engineering and Expeditionary Warfare Center (EXWC) is seeking a self-navigating (autonomous, with semi-autonomous option), self-searching system that will be able to identify eggs in nests for nuisance bird species and provide the operator with the option of treating target eggs. The goal of this system is to extend the use of egg-oiling as a nuisance bird management tool to inaccessible areas (e.g. cliffs, hanger ceilings, towers). Requirements include: - system size suited for nimble maneuvering in areas such as rooftops with sensitive equipment and wiring, building ceilings, power towers, trees, and capability to oil multiple nests during a ~20-30 minute trip - autonomous agents that will sense and explore pertinent regions of interest for bird nests - autonomous navigation that will include local environmental cues and system status to determine safe operating scenarios in real-time - obstacle avoidance of at least two inches and recognition of items such as wires and antennae - human-in-the-loop verification of target nests and initiation of egg oiling treatment; oiling options shall include manual oiling or one-touch automatic oiling treatment - potential target object identification should be achievable within one minute once around a nest - remote oiling treatment of all eggs in a nest should take less than one minute (minimum requirement is that 90% of exposed areas of eggs are coated by oil) - similar treatment success as conventional egg-oiling in terms of parental nest abandonment (<15% abandonment) and egg hatching success (<5% hatching; Ref 6) - capability for acquiring accurate geospatial information, feature counting, and generating a map on the located and treated nests that can be imported (e.g., shapefile, geodatabase, pdf) into DoD management tools post flight - adherence to current DoD information assurance standards and hardware and software compliance (Ref 7) - inexpensive system for field use (estimated < $5-10K per unit), with the goal of commercial procurement near the end of the technology development effort 

PHASE I: Identify and determine the components and platform needed for an autonomous, automated target object identification system for remote egg-oiling. Provide design plans for a working prototype of a remote egg-oiling system, including the autonomous and image-object identification systems that will meet the described need and most current Navy guidance on cybersecurity (e.g., Ref. 7). Conduct preliminary feasibility assessments of the components of the system to identify the limitations of the system (e.g., area covered, number of nests treated), the data that will be needed to develop a fully functioning system, and the time needed to produce a fully-functional prototype. Provide a detailed plan, including a flow chart, for initial prototype testing followed by field demonstration and validation on DoD lands of the egg-oiling system on nuisance birds; the plan shall describe the experimental design and data analysis. Identify the information and data needed to assess the success of the system. Prepare a Phase II plan. 

PHASE II: Conduct prototype testing to demonstrate, refine, and determine the limitations of the system in a controlled environment. Ensure all components are fully operational and demonstrate safe operations in a controlled environment before moving to field testing. Test prototype operation and accuracy in a field environment by oiling eggs of nuisance bird species in different inaccessible locations; coordinate with relevant Navy BASH or installation personnel for field tests; egg “take” permits from the U.S. Fish and Wildlife Service may be needed for the field testing. Compile and analyze relevant data to determine the effectiveness and safety of the system. Generate a summary report describing the results of the prototype testing. Prepare a Phase III development plan to transition the technology to the Navy and DoD. 

PHASE III: Evaluate and qualify the system for Navy use and procurement, potentially including internet, cybersecurity (Ref 7), and approved manufacturing locations to ensure that Navy end-users have access to the system. Manufacture and make the system available for procurement by Navy end-users and providing the system as a service option. If the final system includes an unmanned aircraft system (UAS) component, then the UAS will need to meet the most current DoD and Navy guidance for UAS and operations within the DoD airspace at the time of commercial availability. Other potential users of this system are public and private airports, and any facilities and lands with nuisance bird issues. The components developed for this system can be used for other purposes, such as autonomous navigation of other systems, automated identification of other target objects that may need to be oiled (e.g., hinges, joints), and facilities maintenance needs, such as remote oiling of infrastructure or facilities components that are difficult for personnel to safely reach. 


1: Dalsimer, A.A. "Threatened and Endangered Species on DoD Lands". DoD Natural Resources.

2:  Electronic Code of Federal Regulations, Title 40: Protection of Environment, Part 180 - Tolerances and Exemptions for Pesticide Residues in Food.

3:  Weseloh, D.V.C., Pekarik, C., Havelka, T., Barrett, G., and Reid, J. "Population trends and colony locations of double-crested cormorants in the Canadian Great Lakes and immediately adjacent areas, 1990-2000: A manager’s guide". 2002. J. Great Lakes Res. 28:125-144.

4: Martin, J.M., French, K., and Major, R.E. "The pest status of Australian white ibis (Threskiornis molucca) in urban situations and the effectiveness of egg-oil in reproductive control". 2007. Wildlife Research 34:319-324.

5:  Blackwell, B.F., Seamans, T.W. , Helon, D.A., and Dolbeer, R.A. "Early Loss of Herring Gull Clutches after Egg-Oiling". 2000. Wildlife Society Bulletin. Vol. 28:70-75.

6:  Beaumont, M., Rodrigue, J., Pilotte, C., Chalifour, E., Giroux, J-F. "Behavioral response of Canada geese to egg-oiling and nest removal". The Journal of Wildlife Management. DOI: 10.1002/jwmg.21486.

7: Ross, R., Viscuso, P., Guissanie, G., Dempsey, K., and Riddle, M. "Protecting controlled unclassified information in nonfederal systems and organizations". 2016. NIST Special Publication 800-171, Revision 1.

KEYWORDS: Autonomous Systems; Machine Learning; Cybersecurity; Resource Management 


Jean Pan 

(805) 982-6048 

Timothy Petro 

(805) 982-5577 

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