Multimobile Robot Cooperative Localization Using Ultrawideband Sensor and GPU Acceleration

Xin, Jing; Xie, Guo Wei; Yan, Baixing; Shan, Mao; Gao, Kai

doi:10.1109/tase.2021.3117949

Cited by 9 publications

(2 citation statements)

References 30 publications

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“…Unlike infrared and ultrasound-based beacon location systems, RF waves can penetrate doors and walls, providing ubiquitous coverage of buildings. RF-based localization systems applied to indoor mobile robots typically include: WiFi [ 95 ], Bluetooth [ 96 ], Zigbee [ 97 ], Ultra-Wideband (UWB) [ 98 ], and Radio Frequency Identification (RFID). The advantages and disadvantages of the RF techniques [ 99 ] are shown in Table 2 .…”

Section: Overview Of Single Sensor Sensing Technologiesmentioning

confidence: 99%

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

Liu,

Wang,

Xie

et al. 2024

Sensors

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As a fundamental issue in robotics academia and industry, indoor autonomous mobile robots (AMRs) have been extensively studied. For AMRs, it is crucial to obtain information about their working environment and themselves, which can be realized through sensors and the extraction of corresponding information from the measurements of these sensors. The application of sensing technologies can enable mobile robots to perform localization, mapping, target or obstacle recognition, and motion tasks, etc. This paper reviews sensing technologies for autonomous mobile robots in indoor scenes. The benefits and potential problems of using a single sensor in application are analyzed and compared, and the basic principles and popular algorithms used in processing these sensor data are introduced. In addition, some mainstream technologies of multi-sensor fusion are introduced. Finally, this paper discusses the future development trends in the sensing technology for autonomous mobile robots in indoor scenes, as well as the challenges in the practical application environments.

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Section: Overview Of Single Sensor Sensing Technologiesmentioning

confidence: 99%

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

Liu,

Wang,

Xie

et al. 2024

Sensors

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“…Cooperative localization methods have focused primarily on maneuvering in 2D space [18][19][20][21][22] and particularly using wheeled mobile robots [23][24][25] and vehicles [26,27] due to the complexities involved in the singularity-free representation of 3D orientations. It is, however, critically important to apply CL to 3D vehicle models to improve the localization of networks with homogeneous and heterogeneous air, marine, and ground vehicles.…”

Section: Related Workmentioning

confidence: 99%

Multi-Vehicle Navigation Using Cooperative Localization

Oliveros,

Ashrafiuon

2023

Electronics

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This paper assesses the effectiveness of cooperative localization for improving the performance of closed-loop control systems for networks for autonomous multi-vehicle navigation. Nonlinear dynamic models of two- and three-dimensional vehicles are presented along with their linearized forms. A nonlinear control algorithm is then presented based on the dynamic model. Relative position measurement equations and their linearized forms are introduced. The state and measurement equations are then employed for the propagation and update steps of an EKF-based cooperative localization algorithm. Initially, a series of experiments with networks of quadcopters and mobile robots are presented to validate the performance of cooperative localization for state estimation with the continuous or intermittent presence of absolute measurements or their complete absence. Finally, the performance of the control algorithm is evaluated with and without cooperative localization to demonstrate its effectiveness for improving performance.

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