Fusion of Time-of-Flight Based Sensors with Monocular Cameras for a Robotic Person Follower

• Tipo: Artigo em Revista Científica Internacional
• Data: 2024

Autores

Sarmento, J (Autor) Outra; Filipe Neves Santos (Autor) FEUP; Aguiar, AS (Autor) Outra; Filipe, V (Autor) Outra; Valente, A (Autor) Outra

Revista

Título: Journal of Intelligent and Robotic Systems: Theory and Applications

Vol. 110

Página Final: 30

ISSN: 0921-0296

Editora: Springer Nature

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 5 Citações

Outras Informações

ID Authenticus: P-00Z-WKH

DOI: 10.1007/s10846-023-02037-4

Abstract (EN): Human-robot collaboration (HRC) is becoming increasingly important in advanced production systems, such as those used in industries and agriculture. This type of collaboration can contribute to productivity increase by reducing physical strain on humans, which can lead to reduced injuries and improved morale. One crucial aspect of HRC is the ability of the robot to follow a specific human operator safely. To address this challenge, a novel methodology is proposed that employs monocular vision and ultra-wideband (UWB) transceivers to determine the relative position of a human target with respect to the robot. UWB transceivers are capable of tracking humans with UWB transceivers but exhibit a significant angular error. To reduce this error, monocular cameras with Deep Learning object detection are used to detect humans. The reduction in angular error is achieved through sensor fusion, combining the outputs of both sensors using a histogram-based filter. This filter projects and intersects the measurements from both sources onto a 2D grid. By combining UWB and monocular vision, a remarkable 66.67% reduction in angular error compared to UWB localization alone is achieved. This approach demonstrates an average processing time of 0.0183s and an average localization error of 0.14 meters when tracking a person walking at an average speed of 0.21 m/s. This novel algorithm holds promise for enabling efficient and safe human-robot collaboration, providing a valuable contribution to the field of robotics.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 14