Not listed
PROJECT SUMMARY: RAPID ASSESSMENT OF WILDLAND FIRE POSITION AND PLUME DYNAMICS USING COORDINATED MULTI-UAS SENSINGPIS: SEBASTIAN SCHERER, KATIA SYCARA, IOANNIS GKIOULEKAS (ROBOTICS INSTITUTE, CMU)OVERVIEW:CURRENT APPLICATION OF ROBOTICS TO SITUATIONAL AWARENESS IN WILDLAND FIRES IS LIMITED TO HIGH ALTITUDE OBSERVATIONS FROM UNMANNED AERIAL SYSTEMS (UAS), THUS RESTRICTING THE NEEDED RESOLUTION FOR USABLE SITUATIONAL AWARENESS. WE PROPOSE TO DEVELOP UASS TO SAFELY NAVIGATE NEAR THE GROUND THROUGH DENSE SMOKE AND OBSTACLES TO RECONSTRUCT A HIGH-RESOLUTION PREDICTIVE MODEL OF THE FIRE PLUME AND 3D ENVIRONMENT. SUCH INTEGRATED CAPABILITY WOULD TRANSFORM CURRENT FIREFIGHTING OPERATIONS BY PROVIDING TIMELY INFORMATION ON SAFETY OF ESCAPE ROUTES AND FIRE DIRECTION, THUS DECREASING UNCERTAINTY AND INCREASING FIREFIGHTER SAFETY AS WELL AS ENABLE NEW INSIGHTS FOR FIRE AND SMOKE SCIENCE.INTELLECTUAL MERIT:WE PROPOSE A 3-YEAR COLLABORATIVE INTEGRATED RESEARCH PROJECT THAT BRINGS EXPERTS FROM COMPUTATIONAL IMAGING AND OPTICS, MULTI-ROBOT COLLABORATION, ADAPTIVE SAMPLING, SAFE ROBOT NAVIGATION, AND INTEGRATES FEEDBACK FROM SUBJECT MATTER EXPERTS (SMES) IN THE WILDLAND FIRE MANAGEMENT FIELD. A LARGE PROPORTION OF INJURIES AND LOSS OF FIREFIGHTER LIVES OCCUR BECAUSE OF POOR SITUATIONAL AWARENESS OF THE SAFETY OF ESCAPE ROUTES, ACCURATE PREDICTION OF THE POSITION AND INTENSITY OF THE FIRE. TO ADDRESS LIMITATIONS OF CURRENT TECHNOLOGY WE PROPOSE A THREE-PRONGED APPROACH THAT INTEGRATES: (1) MODEL RECONSTRUCTION OF FIRE PLUME DYNAMICS VIA COLLABORATION OF MULTIPLE UAS, INTEGRATING FOR THE FIRST TIME, NANO-METER TO CENTIMETER BAND TOMOGRAPHY WHERE SIMULTANEOUS SENSOR SEQUENCES MUST BE CAPTURED FROM DIFFERENT POSITIONS, ORIENTATIONS AND TIMES. NO SINGLE WAVE-BAND IS SUFFICIENT TO CAPTURE ALL THE INFORMATION NEEDED TO RECONSTRUCT AND PREDICT THE FIRE PLUME, SO WE WILL USE DIFFERENT SENSING MODALITIES TO DEVELOP AN APPROACH TO TUNE FILTERS FROM DIFFERENT WAVELENGTH BANDS AND SELECT THE SUB-BANDS THAT ARE USEFUL FOR COMMON WILD-FIRES. (2) TO RECONSTRUCT THE FIRE PLUME AND PREDICT FIRE POSITIONING SIMULTANEOUSLY, WE WILL USE ADAPTIVE SAMPLING. GOING BEYOND CURRENT WORK, WE WILL PROVIDE TECHNIQUES BASED ON DISTRIBUTED MIXTURES OF GAUSSIAN PROCESSES THAT ARE EFFICIENT, DECENTRALIZED, CONSIDER ENERGY CONSTRAINTS AND OPERATE WITH NO ASSUMPTION OF KNOWLEDGE OF SPATIAL CORRELATIONS. (3) WE WILL DEVELOP AN APPROACH THAT PROVIDES HIGH RESOLUTION SENSING WITH LOW-SWAP-C (SIZE, WEIGHT, POWER, AND COST) THROUGH OBSCURANTS (SMOKE), AND CAN INCORPORATE PERCEPTUAL UNCERTAINTY, MOTION UNCERTAINTY FROM ONBOARD SENSORS, AND FUSE ALL SOURCES OF UNCERTAINTY AND DEGRADATION INTO A RISK MAP THAT WILL BE USED FOR RISK AWARE SAFE MOTION PLANNING AND CONTROL FOR THE FIRST TIME. WE WILL EVALUATE OUR INTEGRATED RESEARCH APPROACH AND RESULTING SYSTEM IN SIMULATION AND IN FIELD EXPERIMENTS INCLUDING PRESCRIBED BURNS OPERATED BY THE WILDLAND FIRE MANAGERS, WHERE FIRES ARE DELIBERATELY STARTED AND MON,ITORED.?BROADER IMPACTS:THE TECHNOLOGIES DEVELOPED IN THE PROPOSED WORK WILL ENABLE UAS TO OPERATE IN LOCATIONS CURRENTLY INACCESSIBLE DUE TO VISUAL OBSCURANTS AND OBSTACLES. THE ENHANCED SITUATIONAL AWARENESS WILL INCREASE PRODUCTIVITY AND SAFETY OF FIREFIGHTERS. THE INTEGRATION OF OPTIMIZED SENSOR TECHNOLOGY, FIRE PLUME PREDICTION AND RESILIENT OPERATION IN SMOKE, INCLUDING OTHER VISUAL DEGRADA- TION, WILL HAVE SIGNIFICANT IMPACT IN WILDLAND FIRE MANAGEMENT AND OTHER DISASTERS. ADDITIONALLY, THE PROPOSED MULTI-ROBOT DEPLOYMENT ALGORITHMS FOR EFFICIENT GATHERING OF OBSERVATIONS CAN BE APPLIED TO MANY RELATED PROBLEMS SUCH AS ENVIRONMENTAL MONITORING AND SEARCH & RESCUE. THE DATA AND SOFTWARE RESULTING FROM THE PROJECT WILL BE PUBLICLY AVAILABLE THROUGH OPEN SOURCE LICENSES. ADDITIONALLY, THE PIS WILL INTEGRATE THE RESEARCH RESULTS IN THEIR RESEARCH AND EDUCATION ACTIVITIES VIA CAPSTONE PROJECTS, SEMINARS AND BROADEN THE PARTICIPATION OF UNDERREPRESENTED MINORITIES WITH ADDITIONAL MEANS, SUCH AS SUMMER INTERNSHIPS.
$1.2m 2/7/23