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ABOUT THE COURSE:
This course will provide detailed introduction of Environment perception algorithm block chain for autonomous platforms such as, Drone/Unmanned aerial vehicles (UAVs), Autonomous driver assistance systems (ADAS), Unmanned ground vehicles (UGVs) etc. Autonomous platforms gather perception information of the environment through multiple sensors measurements such as, Radar (FMCW/Phased array/Pulse Doppler), EO/IRST, Multi-function Camera and Lidar (MFCL), ultrasonics etc. This course will encompass 3 major object/target information processing stages as part of entire perception algorithm modules - Data-association and Multi Object tracking, Multi Sensor data and information fusion and Target classification. The course will focus on fundamentals of various estimation techniques like Maximum likelihood, Maximum-a- posteriori and Kalman filtering and its application to target tracking and sensor fusion.
PREREQUISITES: Primarily for ME/Ph.D with Control system or Signal Processing related specialization. However, BE (4th year) in EE, ETC or Automobile and Aerospace Engineering can also opt it as open elective.
INDUSTRY SUPPORT:
- Automotive Industry working on Software define Vehicle (Bosch, Aumivio, Qualcomm, Nvidia, APTiV, Denso, BMW, Mercedes Benz, VW, Toyota, Ford etc.)
- Aerospace Industry (DRDO Labs – LRDE, DARE, DRDL/RCI Hyderabad, NSTL vizag etc.), HAL Hyderabad, BEL Bangalore, Thales, Safran Defense and Electronics, Northrop Grunman, Collins, Honeywell etc.
This course will provide detailed introduction of Environment perception algorithm block chain for autonomous platforms such as, Drone/Unmanned aerial vehicles (UAVs), Autonomous driver assistance systems (ADAS), Unmanned ground vehicles (UGVs) etc. Autonomous platforms gather perception information of the environment through multiple sensors measurements such as, Radar (FMCW/Phased array/Pulse Doppler), EO/IRST, Multi-function Camera and Lidar (MFCL), ultrasonics etc. This course will encompass 3 major object/target information processing stages as part of entire perception algorithm modules - Data-association and Multi Object tracking, Multi Sensor data and information fusion and Target classification. The course will focus on fundamentals of various estimation techniques like Maximum likelihood, Maximum-a- posteriori and Kalman filtering and its application to target tracking and sensor fusion.
PREREQUISITES: Primarily for ME/Ph.D with Control system or Signal Processing related specialization. However, BE (4th year) in EE, ETC or Automobile and Aerospace Engineering can also opt it as open elective.
INDUSTRY SUPPORT:
- Automotive Industry working on Software define Vehicle (Bosch, Aumivio, Qualcomm, Nvidia, APTiV, Denso, BMW, Mercedes Benz, VW, Toyota, Ford etc.)
- Aerospace Industry (DRDO Labs – LRDE, DARE, DRDL/RCI Hyderabad, NSTL vizag etc.), HAL Hyderabad, BEL Bangalore, Thales, Safran Defense and Electronics, Northrop Grunman, Collins, Honeywell etc.
