2023/06/26 by Luke Robinson, Daniele De Martini, Robinson, Luke +5
Computer Science · #Advanced Image and Video Retrieval Techniques #Advanced Vision and Imaging #FOS: Computer and information sciences #Robotics (cs.RO) #Video Surveillance and Tracking Methods
paper · pdf · doi:10.48550/arxiv.2306.14848
openalex publication_date 2023/06/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This work proposes a fast deployment pipeline for visually-servoed robots which does not assume anything about either the robot - e.g. sizes, colour or the presence of markers - or the deployment environment. In this, accurate estimation of robot orientation is crucial for successful navigation in complex environments; manual labelling of angular values is, though, time-consuming and possibly hard to perform. For this reason, we propose a weakly supervised pipeline that can produce a vast amount of data in a small amount of time. We evaluate our approach on a dataset of remote camera images captured in various indoor environments demonstrating high tracking performances when integrated into a fully-autonomous pipeline with a simple controller. With this, we then analyse the data requirement of our approach, showing how it is possible to deploy a new robot in a new environment in less than 30.00 min.