A multi-sensorial simultaneous Localization and Mapping (SLAM) System for Low-cost Micro aerial vehicles in Gps-denied ENV Ironments

A multi-sensorial simultaneous Localization and Mapping (SLAM) System for Low-cost Micro aerial vehicles in Gps-denied ENV Ironments

A multi-sensor synchronous location mapping system for low-priced micro-aircraft designed in GPS-free environment

Academic Editor: Gonzalo Pajares Martinsanz
Received: January 25, 2017; accepted: April 5, 2017; release time: April 8 201

Abstract:one of the main challenges of aerial robots navigation in indoor or gps-denied environments are position Estimati On using only the available onboard sensors. This paper presents a simultaneous Localization and Mapping (SLAM) system that remotely calculates the pose and environmen T map of different low-cost commercial aerial platforms, whose onboard computing capacity is usually limited. The proposed system adapts to the sensory con?guration of the aerial robot, by integrating different state-of-the art SLAM Methods based on vision, laser and/or inertial measurements using an Extended Kalman Filter (EKF). To does this, a minimum onboard sensory con?guration are supposed, consisting of a monocular camera, an inertial measurement Unit (IMU) and an altimeter. It allows to improve the results of well-known monocular visual SLAM methods (Lsd-slam and Orb-slam is tested and compare Solving scale ambiguity and providing additional information to the EKF. When payload anD Computational capabilities permit, a 2D laser sensor can be easily incorporated to the SLAM system, obtaining a local 2. 5D map and a footprint estimation of the robot position that improves the 6D pose estimation through the EKF. We present some experimental results with a different commercial platforms, and validate the system by applying it to th Eir position control.

Summary: One of the major challenges in aerial robots in environments without GPS signals is to use only the location estimates of available airborne sensors. This paper presents a simultaneous mapping and positioning (SLAM) system, which can calculate the posture and environment map of different low-priced commercial aviation platforms remotely, because the capability of airborne computing is usually limited. The system is suitable for airborne robotic sensor configurations by fusing different advanced slam methods including visual slam, LiDAR Slam and/or using EKF inertial measurements. To do this, a minimal airborne sensing configuration is possible, including a monocular camera, an inertial measurement unit (IMU), and a altimeter.

A multi-sensorial simultaneous Localization and Mapping (SLAM) System for Low-cost Micro aerial vehicles in Gps-denied ENV Ironments