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Surveillance Robot
Autonomous indoor navigation robot with 93% obstacle avoidance accuracy
C++Raspberry PiOpenCVPython
The Problem
Indoor surveillance requires expensive commercial solutions. DIY alternatives lack reliability and autonomous navigation.
The Approach
Built indoor navigation/control system using C++ and Raspberry Pi. Implemented computer vision for obstacle detection and path planning algorithms for autonomous movement.
The Impact
Achieved 93% obstacle-avoidance accuracy during autonomous runs. Cost-effective alternative to commercial surveillance systems.