1 / 7

Intelligent Autonomy Update

Intelligent Autonomy Update. Marc Steinberg Office of Naval Research (703) 696 – 5115, marc_steinberg@onr.navy.mil Naval Air Systems Command (301) 342 – 8567, marc.steinberg@navy.mil SAE Control & Guidance Committee Meeting, 2 March, 2005. Intelligent Autonomy Future Vision.

pillan
Download Presentation

Intelligent Autonomy Update

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Intelligent Autonomy Update Marc Steinberg Office of Naval Research (703) 696 – 5115, marc_steinberg@onr.navy.mil Naval Air Systems Command (301) 342 – 8567, marc.steinberg@navy.mil SAE Control & Guidance Committee Meeting, 2 March, 2005

  2. Intelligent Autonomy Future Vision External C4I, Data Filtering Mixed-Initiative Human Interface Common Operational Picture High Level Mission Requirements/ROE Common Information Management Multi-Vehicle Mission Planning Management of 5-10 UxV’s Task Scheduling, Routing, Constraints, Priorities Share Mission Relevant Info Report Status Multiple Types of Vehicle Interfaces/Comms UGV Locally Controlled, Shares Info UUV Local Planning & SA UAV Local Planning & SA USV Local Planning & SA Local Task Negotiation, Information Sharing

  3. MOUT Site DemonstrationUniv. of Penn., Georgia Tech., USC, BBN, Mobile Intelligence • Summary • Team planning mechanisms geared towards maximizing communications capabilities in adverse conditions while on the move. • Integrated mission specification capabilities for parsing the tasks of overall mission objectives and mapping them onto heterogeneous UxV’s • V&V of autonomous algorithms • Joint with DARPA • Accomplishments • Integration of large number of heterogeneous UxV’s with different lower-level autonomy software • Framework integrating communications, perception, and execution for UxV’s • New algorithm development & implementation for communication sensitive behaviors, heterogeneous UxV tasking, distributed SA, and V&V of autonomous systems • Completed Demo at MOUT Site • Operator tasks multiple types of UAV’s and UGV’s with high-level commands • Mission execution while maintaining communication constraints • Future Work • Case-Based Reasoning & Multi-UxV Task Allocation to support mission specification • Extend V&V approach to test IA systems

  4. Risk-Aware Mixed-Initiative Dynamic Replanning DemoDraper Laboratory/CRA • Summary • Single-operator mission management of multiple heterogeneous unmanned vehicles • Extend UUV software w/ increased autonomy on-board UUV & increased dynamic retasking capability for missions w/ comms constraints • Integration with on-board vehicle sensors & external systems N Region 3 Region 4 Region 2 Keep-out Region 1 No Comms Target region • Accomplishments • Initial software design & implementation • Integration of initial versions of SA, situation assessment, mixed-initiative interface, control station planning, UUV on-board planning/SA. • Initial integration with existing UUV lower-level autonomous control software • Usability analysis by NAVAIR & NSWC to recommend improvements • Completed Dynamic Replanning Demo w/ high-fidelity UUV simulation • Single UUV, UAV as comm link • Operator provides high-level tasking/constraints • Autonomously generates plan of activities for UUV to start the mission, transit, search shoreline for particular target classes, end mission • Monitors execution • Future Work • Extend to increase UAV/UUV cooperation, complexity of tasking, integration with other systems, & realism of simulation • In-water demonstration

  5. Mission Control for Multiple UxV’s DemonstrationBAE Systems, Aptima, MIT, BU, Univ. of Minnesota • Summary • Allocates tasks based on operator high-level team tasking and constraints • Determines team & individual vehicle tactics to achieve objectives • Schedules activities for heterogeneous resources • Inputs to lower-level vehicle planners • Cooperation w/ realistic comms limitations • Accomplishments • Extended Mission Control System (MCS) to provide tasking and routing for naval autonomous systems. • Allocates tasks to vehicles including cooperative search and data collection • Constraints include time windows, precedence constraints, and no activity zones • Tasks prioritized as mandatory, high, med, or low. Drops lower priority tasks if not feasible. • Multi-UxV Simulation Demonstration • Firescout, J-UCAS, BAMS, USV • Operator provides high-level team tasking, ROE’s, & constraints • Replans following changes in environment or new tasking • Future Work • Simulation Demonstration in communication limited environment (joint with Air Force) • Local planning under constraints on vehicle when outside of communication

  6. Maritime Image UnderstandingNorthrop/Carnegie Mellon University • Summary • Maritime Image Understanding for autonomous sensor-directed dynamic replanning • Supports low elevation UUV mast with no mechanical stabilization of image • Detects, classifies, and tracks targets • Joint with DARPA Completed In-Water Demo on Spartan USV • Accomplishments • Reliable surface object detection in clear and hazy conditions • Image stabilization using software only • Low false alarm rate for shoreline man-made object detection • Interesting object detection to direct data collection • Real-Time maritime scene segmentation/high speed video array & limited classification capability Surface Object Detection & Tracking Shoreline Detection • Future Work • Integration with on-board dynamic replanning software to enable replanning with sensed data • Additional in-water experimentation • Improved robustness Shoreline Man-Made Object Detection

  7. com hellfi SAR1 EO eng Intelligent Control & Autonomous Replanning of Unmanned Systems (ICARUS) - Lockheed • Summary • Integrated suite of components to enable rapid highly automated and fully autonomous mission planning/replanning by high-level objectives • Determines optimized route that meets all constraints & mission objectives while also optimizing secondary priorities • Accomplishments • Integrated Multi-UV Task Allocation, Replanning, Replan Assessment, Information/Alert Management, Operator Interface, & Lower level GNC components • Objectives incorporated include search for stationary & mobile targets, EO/IR, SAR, Loiter, Steer-Point, Communication • Constraints incorporated included no-fly zones and LOS comms requirements (moving & stationary) • Completed Simulation Demonstration & Evaluation by 2 Navy & 2 Marine Corps Operators with 7 UAV’s (Firescout, BAMS, Future ISR) • Replanning for Dynamic Mission Events • New/Dropped Mission Tasks • Change in order of tasks • Failures/Weather/changes in environment • Future Work • Integration with naval control station • Simulation Demonstration in warfare environment at NAVAIR • Increased robustness/integration

More Related