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Replanning and Operator Situation Awareness Tools for Operation of Unmanned Systems in Complex Airspaces and Waterspaces
Navy SBIR 2009.1 - Topic N091-082 ONR - Mrs. Tracy Frost - [email protected] Opens: December 8, 2008 - Closes: January 14, 2009 N091-082 TITLE: Replanning and Operator Situation Awareness Tools for Operation of Unmanned Systems in Complex Airspaces and Waterspaces TECHNOLOGY AREAS: Air Platform, Ground/Sea Vehicles, Human Systems ACQUISITION PROGRAM: Broad Area Maritime Surveillance, I, PMA-262; Joint Mission Planning System The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), which controls the export and import of defense-related material and services. Offerors must disclose any proposed use of foreign nationals, their country of origin, and what tasks each would accomplish in the statement of work in accordance with section 3.5.b.(7) of the solicitation. OBJECTIVE: To develop and demonstrate tools to assist an unmanned systems operator in rapid replanning and mission execution of naval unmanned system missions to take into complex airspace and/or waterspace rules, control procedures, weather and traffic conditions, and mission requirements. This includes operator interface approaches for supervisory control of unmanned systems to maintain operator situation awareness of complex airspace/waterspace procedures that may change over time. It also includes mixed-initiative approaches and automated planning tools that take into account both airspace/waterspace issues and mission issues. Note that the objective of this topic is to provide support for operators of unmanned systems and not an air traffic controller who is managing a whole airspace. DESCRIPTION: Increasingly, the operators of unmanned systems are being given dynamic tasking that can change rapidly over the course of a mission. In this case, operators may need to develop new mission plans rapidly to respond to requests for unmanned system services in support of tactical needs. One of the challenges in doing this is the need to operate in very complex and congested air or water spaces. To do this, operators may work closely with controllers who have responsibility for that space and who may not fully understand all of the limitations of the unmanned systems. Operators must maintain a high degree of awareness with all relevant control procedures for both manned and unmanned systems in that space and ensure that new plans will have adequate deconfliction with other assets and also take into account weather conditions. Further, not all the events that occur in a space are predictable. For example, other entities may violate their restrictions and that may lead to the operator of the unmanned system needing to make a rapid change. Operators also must ensure that the vehicle will not violate rules and procedures even in a lost communications situation. This situation will become even more complicated in the future where operators may have responsibility for multiple heterogeneous unmanned systems and systems that have higher degrees of autonomy. This topic will examine tools that can be used to support the operator in maintaining situation awareness of the relevant airspace and waterspace issues and performing rapid mission replanning that takes into account airspace procedures, deconfliction, and weather issues. There have been a number of programs that have examined human interface and automated planning and replanning tools for supervisory control of unmanned systems. However, these efforts have typically dealt with airspace and waterspace issues only in a very simple way, such as by designating a specific operations box with keep-out zones. Additional development is needed to account for both mission requirements and the full range of airspace/waterspace considerations and to ensure operators have sufficient situation awareness and ability to chose among different safety options. The factors that would need to be taken into account include space restrictions that may vary based on vehicle equipage, vehicle performance capabilities and status, threats, weather, air traffic, and other mission participant�s (manned/unmanned) systems capability and status. For this topic, a capability of interest would include (1) Automated planning and replanning tools that take into account all of the above factors, (2) Automated analysis of plan alternatives and their potential impact on safety, (3) Mission displays for supervisory control of unmanned systems that take into account all of the above factors and provide the operator with an understanding of the plans generated by the automation. Technology approaches that may be of relevance to address this type of problem include mixed-initiative interfaces, ecological interface design, displays for providing operator information requirements at higher levels of abstraction, trend and configural displays, approaches for measuring trust in automation, and planning approaches that can incorporate complex temporal and spatial requirements and generate solutions that can be proven safe. The latter should allow incorporation of both hard constraints and also ways to positively impact on the behavior of the autonomous system (e.g., a preference for flying through a part of the flight envelope that is not a hard constraint). This should be addressed for both single and multiple heterogeneous vehicles and take advantage of existing weather and airspace classification tools that can provide data. For multiple unmanned vehicle, it would be of value to have approaches that can reduce the amount of separation for vehicles operating in the same space. It should also address vehicles with different levels of on-board autonomy and take communication limitations into account. Also, of interest are future uses of unmanned systems that may operate in crowded air and water spaces around naval ships for purposes such as force protection. Approaches to develop new sensors or communications approaches are outside the scope of this effort. Due to the potential impact on safety, it will be important that there be viable approaches to certify the particular approach being proposed. In addition, operator trust will play an important role in the usefulness of these tools and that must be considered in the development of the approach. PHASE I: Develop an initial version of the proposed approach for a limited set of air platform types and airspace situations with sufficient functionality to demonstrate feasibility and allow some limited experimentation. Experiments with algorithms may be done with low-fidelity simulation elements to show closed loop performance and robustness. Simulation may include some limited-complexity vehicle models, sensor models, and communications models, depending on what would be most suitable to examine the particular approach. Human interface concepts for that particular control approach may be examined with a simple mock-up or with some limited functionality to get feedback from naval operators and domain experts. Develop metrics to evaluate the system in Phase II and determine how the approach could interface with naval control stations and mission planning tools. Examples of relevant metrics include Workload (NASA TLX or CHR), Situation Awareness (SAGAT), response or reaction time, task time, number of entities dealt with simultaneously, number of operator interactions per time or event, decision accuracy, usability, and trust (Lee and Moray Trust Scale). PHASE II: Further develop the proposed approach for a broader set of airspace and waterspace situations and system types in a more complex dynamic and unstructured environment and integrate them with a medium-fidelity simulation and sufficient autonomy components to perform laboratory operator in-the-loop experiments and comparison with benchmarks. If feasible, experiments may also be conducted with the use of inexpensive unmanned vehicles. Experiments should include a focus on determining the sensitivity of the system to a variety of factors such as communication degradation, operator workload, and complexity of the environment. Revise evaluation metrics as necessary PHASE III: Integrate the software with a naval unmanned air system control station and/or the Joint Mission Planning System (JMPS) and participate in integrated demonstrations of multi-vehicle operations. PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: This capability could be used in a broad range of civilian applications of unmanned systems including use by first responders and homeland security and in other applications involving management of automated systems, such as industrial applications. REFERENCES: 2. Parasuraman, R., Barnes, M., Cosenzo, K., "Adaptive Automation for Human-Robot Teaming in Future Command and Control Systems," The International C2 Journal, Vol 1, No 2, pp. 43�68 3. Kilgore, R., Harper, K., Cummings, M., and Nehme, C., "Mission Planning and Monitoring for Heterogeneous Unmanned Vehicle Teams: A Human-Centered Perspective" Proceedings of AIAA Infotech, 2007. 4. Lingang, M. et al, "Human-Automation Collaboration in Dynamic Mission Planning: A Challenge Requiring an Ecological Approach," Human Factors and Ergonomics Society Annual Meeting, 2006. 5. Lee, J.D. and See, K.A. (2004), "Trust in automation: Designing for appropriate reliance," Human Factors, 46, 50-80. 6. Vicente, K. J. and J. Rasmussen (1992). "Ecological Interface Design: Theoretical Foundations." IEEE Transactions on Systems, Man, and Cybernetics 22(4): 589-606. 7. Ahmadzadeh , A., Buchman , G., Cheng , P., Jadbabaie, A., Keller, J., Kumar, V., Pappas, G., "Cooperative control of UAVs for Search and Coverage" Proceedings of the AUVSI Conference on Unmanned Systems, 2006. 8. A. Richards, J. How, "Mixed-integer Programming for Control," In proceedings of the American Control Conference, 2005. 9. Lavalle, S., Planning Algorithms, Cambridge University Press, 2006. 10. Steinberg, M., "Flight and In-Water Experiments of Autonomy and Human Interface Technologies with Multiple Unmanned Systems," AUVSI Unmanned Systems North America, 2008. 11. A. Thurling, "An Operator�s Requirements for Detect, Sense, and Avoid," AUVSI Unmanned Systems North America, 2007. 12. Samad and Balas (Eds.), Software-Enabled Control, John Wiley, March 2003. 13. C. Tomlin and M. Greenstreet, Editors. Hybrid Systems: Computation and Control, Springer-Verlag, Lecture Notes in Computer Science (LNCS) 2289, March 2002. 14. P. Cheng, V. Kumar, "Sampling-based Falsification and Verification of Controllers for Continuous Dynamic Systems", The Seventh International Workshop on the Algorithmic Foundations of Robotics, 2006 KEYWORDS: human interface; unmanned systems; airspace management
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