Towards S-NAMO: Socially-aware Navigation Among Movable Obstacles

International audienc

TOWARDS MULTIMODAL OMNIDIRECTIONAL OBSTACLE DETECTION FOR AUTONOMOUS UNMANNED AERIAL VEHICLES

Limiting factors for increasing autonomy and complexity of truly autonomous systems (without external sensing and control) are onboard sensing and onboard processing power. In this paper, we propose a hardware setup and processing pipeline that allows a fully autonomous UAV to perceive obstacles in (almost) all directions in its surroundings. Different sensor modalities are applied in order take into account the different characteristics of obstacles that can commonly be found in typical UAV applications. We provide a complete overview on the implemented system and present experimental results as a proof of concept