Avoiding Moving Obstacles during Visual Navigation

Moving obstacle avoidance is a fundamental requirement for any robot operating in real environments, where pedestrians, bicycles and cars are present. In this work, we design and validate a new approach that takes explicitly into account obstacle velocities, to achieve safe visual navigation in outdoor scenarios. A wheeled vehicle, equipped with an actuated pinhole camera and with a lidar, must follow a path represented by key images, without colliding with the obstacles. To estimate the obstacle velocities, we design a Kalman-based observer. Then, we adapt the tentacles designed in [1], to take into account the predicted obstacle positions. Finally, we validate our approach in a series of simulated and real experiments, showing that when the obstacle velocities are considered, the robot behaviour is safer, smoother, and faster than when it is not.