Range-aided ego-centric collaborative pose estimation for multiple robots. (15th September 2022)

• Record Type: Journal Article
• Authors: Papadimitriou, Andreas; Mansouri, Sina Sharif; Nikolakopoulos, George
• Is Part Of: Expert systems with applications. Volume 202(2022)
• Publication Date: 2022-09-15
• Subjects: Relative pose estimation -- UWB -- Ego-centric estimation -- Sensor fusion; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2022.117052
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: Robots' simultaneous relative pose estimation has become an essential step in most robotic-oriented problems, such as map merging, collision avoidance, path planning, and multi-Simultaneous Localization and Mapping (SLAM). This article addresses the problem of 3D and ego-centric relative pose estimation for a team of robots equipped with Ultra WideBand (UWB) nodes. More specifically, the article introduces a novel optimization framework to obtain pose information based on the embodiment of UWB ranges, without relying on any fixed external infrastructure configuration of UWB anchors on the surrounding environment. In the proposed method, we demonstrate the validity through the utilization of a Micro Aerial Vehicle (MAV) and a ground vehicle that are equipped with multiple UWB transceivers, and each platform simultaneously acts as a based anchor for the other platform for extracting an ego-centric position estimation of the UWB nodes. Additionally, for the pose estimation, the obtained information is fused with the onboard Inertial Measurement Unit (IMU) measurements on each of the considered robotic platforms. Finally, the efficacy of the proposed theoretical framework is evaluated in multiple experiments, where the aerial and ground platforms are simultaneously and separately navigating, and the ego-centric collaborative pose-estimation is compared with a VICON ground truth positioning system. Highlights: Multiple robots relative pose estimation. UWB and IMU fusion. No requirement for fixed localization infrastructure. Flexible ego-centric position estimation.