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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.