We are exploring efficient guidance, navigation and control algorithms using sensor fusion, visual odometery, deep learning techniques for mobile robots in indoor applications.
Machine Learning for Microcontrollers
We are exploring efficient (SLaP) Machine Learning algorithms for audio, sound, IMU signals, etc. detection and classification.
We are exploring efficient UAV guidance, navigation and control algorithms for UAVs in urban applications. Development of a low cost modularized UAV testbed for HIL simulations. Also effective use of mini FLIR and hyper-spectral cameras for people, vehicle and terrain detection. Use of acoustic for target classification and localization. Autonomous indoor navigation based on sensor fusion.
Efficient router design for VC channel buffer utilization, VC allocation, Routing algorithms, Mapping Algorithms, etc.
Development of pedestrian count and tracking algorithms, pedestrian-vehicle conflict detection system.