Teledrive: An Embodied AI based Telepresence System

TL;DR

Teledrive presents a hardware-agnostic telepresence platform that integrates AreaGoal and embodied AI navigation with speech-based HRI over edge-Cloud WebRTC, enabling remote caregivers to guide robots into rough target areas in unknown premises. The architecture combines PointNav, ObjectNav, and a novel AreaNav module, supported by a Visual Semantic Map and a Spatial Relational Graph to achieve robust long-horizon navigation and object searching, validated in Habitat simulations and real-world deployments. A multi-party, browser-based UI and an operator dialogue framework facilitate hands-free, scalable telepresence, while a dedicated person-following capability extends utility for caregiver monitoring. The results show strong AreaGoal performance, competitive PointNav/ObjectNav baselines, and positive usability feedback, underscoring the system’s potential for remote care, isolation wards, and workplace supervision scenarios.

Abstract

This article presents Teledrive, a telepresence robotic system with embodied AI features that empowers an operator to navigate the telerobot in any unknown remote place with minimal human intervention. We conceive Teledrive in the context of democratizing remote care-giving for elderly citizens as well as for isolated patients, affected by contagious diseases. In particular, this paper focuses on the problem of navigating to a rough target area (like bedroom or kitchen) rather than pre-specified point destinations. This ushers in a unique AreaGoal based navigation feature, which has not been explored in depth in the contemporary solutions. Further, we describe an edge computing-based software system built on a WebRTC-based communication framework to realize the aforementioned scheme through an easy-to-use speech-based human-robot interaction. Moreover, to enhance the ease of operation for the remote caregiver, we incorporate a person following feature, whereby a robot follows a person on the move in its premises as directed by the operator. Moreover, the system presented is loosely coupled with specific robot hardware, unlike the existing solutions. We have evaluated the efficacy of the proposed system through baseline experiments, user study, and real-life deployment.

Figures (20)

• Figure 1: 'Teledrive' system is given AreaGoal-based navigation instruction in remote caregiving use case.
• Figure 2: Edge-Cloud topology of the distributed networked Embodied AI of Teledrive.
• Figure 3: System architecture of Teledrive showing distributed set of building blocks spread across four entities -- master device, cloud server, robot (avatar), and robot-edge.
• Figure 4: Embedding of human-robot interaction mechanism into Teledrive.
• Figure 5: Method overview of PointNav Module.