Abstract: Unmanned aerial and ground vehicles (UAVs and UGVs) today excel at autonomous navigation due to their reliance on GNSS sensors. GNSS sensors are an unviable option for navigation in indoor environments due to lack of direct line-of- sight with satellites and lack of environmental awareness. This project proposes an integrated solution for localization of the vehicle in an indoor environment, path planning and obstacle avoidance. The proposed system uses range imaging sensors for depth estimation and visual odometry (visual simultaneous localization and mapping) for pose estimation. Simulations and realworld tests show that the proposed system can be used in a complex indoor environment with optimal lighting conditions and low to medium clutter of obstacles.

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