Multi-Agent Relative Pose Estimation with UWB and Constrained Communications

Fishberg, Andrew; How, Jonathan P.

doi:10.1109/iros47612.2022.9982005

Cited by 19 publications

(5 citation statements)

References 39 publications

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“…Ultra-Wideband (UWB) technology presents a promising solution. Fishberg and How [54] developed a 3-DOF relative 2D pose estimation system among robots, achieving improvements in mean position error solely based on UWB measurements. Cossette et al [55] introduced a method for estimating relative orientations using UWB distance measurements, demonstrating that estimation accuracy can be increased by optimizing the formation geometry of robot formation.…”

Section: Direct Pose Estimationmentioning

confidence: 99%

Easy Rocap: A Low-Cost and Easy-to-Use Motion Capture System for Drones

Wang,

Chen,

et al. 2024

Drones

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Fast and accurate pose estimation is essential for the local motion control of robots such as drones. At present, camera-based motion capture (Mocap) systems are mostly used by robots. However, this kind of Mocap system is easily affected by light noise and camera occlusion, and the cost of common commercial Mocap systems is high. To address these challenges, we propose Easy Rocap, a low-cost, open-source robot motion capture system, which can quickly and robustly capture the accurate position and orientation of the robot. Firstly, based on training a real-time object detector, an object-filtering algorithm using class and confidence is designed to eliminate false detections. Secondly, multiple-object tracking (MOT) is applied to maintain the continuity of the trajectories, and the epipolar constraint is applied to multi-view correspondences. Finally, the calibrated multi-view cameras are used to calculate the 3D coordinates of the markers and effectively estimate the 3D pose of the target robot. Our system takes in real-time multi-camera data streams, making it easy to integrate into the robot system. In the simulation scenario experiment, the average position estimation error of the method is less than 0.008 m, and the average orientation error is less than 0.65 degrees. In the real scenario experiment, we compared the localization results of our method with the advanced LiDAR-Inertial Simultaneous Localization and Mapping (SLAM) algorithm. According to the experimental results, SLAM generates drifts during turns, while our method can overcome the drifts and accumulated errors of SLAM, making the trajectory more stable and accurate. In addition, the pose estimation speed of our system can reach 30 Hz.

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Section: Direct Pose Estimationmentioning

confidence: 99%

Easy Rocap: A Low-Cost and Easy-to-Use Motion Capture System for Drones

Wang,

Chen,

et al. 2024

Drones

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show abstract

“…various configuration choices, the equilateral triangle sensor configuration exhibits a lower and more uniformly distributed GDOP, indicating higher average accuracy and improved accuracy distribution. For instance, studies [4] and [9] investigate relative position and pose estimation using four UWB sensors onboard.…”

Section: B Sensor Configuration 1) Minimum Number Of Onboard Sensorsmentioning

confidence: 99%

Infrastructure-Free Relative Localization: System Modeling, Algorithm Design, Performance Analysis, and Field Tests

Gao,

Cheng,

Qiu

et al. 2024

Preprint

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Relative localization is an essential part of autonomous multi-agent systems. Existing methods often require real-time communications, pre-installed infrastructure, and substantial computational resources. In this study, drawing inspiration from the collective behaviors of primitive animals, we propose an infrastructure-free 2D distributed relative localization framework utilizing onboard ranging sensors. We start with system modeling, based on which optimal sensor configuration and algorithm design are conducted. Subsequently, we perform a thorough performance analysis and validate the overall system design through field tests using unmanned ground vehicles (UGVs) equipped with ultra-wideband (UWB) ranging sensors and micro-controller units onboard. Contributions include the following: the geometric dilution of precision (GDOP) and Cramér-Rao lower bound (CRLB) are derived; a novel Euclidean distance matrix (EDM)-based trilateration algorithm and a maximum likelihood estimation algorithm are proposed; and comprehensive simulation and field tests are conducted to validate the viability of the proposed framework. Two use cases are considered: to localize a target sensor and to localize an agent. The theoretical, numerical, and experimental results will shed light on the design and optimization of relative localization systems, and our proposed framework holds potential for future extensions to 3D scenarios, different unmanned vehicle platforms, and multi-robot cooperative systems.

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“…2. Therefore, this can be understood as a generalization of the positioning method proposed in [21] and [22] with the important difference being that it measures distance differences instead of estimating the distances using RTT on UWB. x y using:…”

Section: A One Group Of Synchronized Reference Nodesmentioning

confidence: 99%

“…The results of the measurements are then used to estimate the displacement and rotation angle of the second container relative to the first one. In addition, the article [22] contains the results of a study on the relative positioning of robots with a more sophisticated configuration of four UWB sensors. The mobile robots are able to measure the distances using the RTT method, but the results of the measurements are weighted to reduce the impact of less accurate range data collected using obstructed antennas.…”

Section: Introductionmentioning

confidence: 99%

Position and Orientation Estimation in Radio Network With Groups of Locally Synchronized Nodes

Sadowski,

Stefanski

2023

IEEE Access

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This article presents a positioning system with groups of locally synchronized nodes. A mobile object is equipped with a group of several synchronized receivers that are able to measure the difference in the time of arrival of signals from reference transmitters. The reference transmitters are synchronized only in local groups, with no global synchronization between groups. It is assumed that the synchronous operation of transmitters and receivers in groups does not allow for the phase-coherent emission and reception of signals, making beamforming and angle of arrival estimation impossible. The structure of the positioning system and the equations for estimating the position and orientation angle are presented, along with the Gauss-Newton algorithm for iteratively estimating the coordinates and orientation of the mobile object. The possible accuracy of the proposed solution is evaluated using dilution of precision and the Cramer-Rao lower bound. The analysis showed that although the quality of the position estimation in the proposed solution is highly dependent on the mutual location of the reference transmitters and the mobile object, the orientation angle can be estimated highly accurately, almost regardless of the mobile object location.

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Multi-Agent Relative Pose Estimation with UWB and Constrained Communications

Cited by 19 publications

References 39 publications

Easy Rocap: A Low-Cost and Easy-to-Use Motion Capture System for Drones

Easy Rocap: A Low-Cost and Easy-to-Use Motion Capture System for Drones

Infrastructure-Free Relative Localization: System Modeling, Algorithm Design, Performance Analysis, and Field Tests

Position and Orientation Estimation in Radio Network With Groups of Locally Synchronized Nodes

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