[Paper Review] Co-Robots as Care Robots

Oliver Bendel|arXiv (Cornell University)|Jan 1, 2020

Social Robot Interaction and HRI21 references2 citations

TL;DR

This paper evaluates the Lio co-robot, a mobile, two-armed service robot with human-robot interaction (HRI) capabilities, in long-term care and rehabilitation settings. Based on qualitative studies in nursing and retirement homes, it demonstrates that co-robots like Lio enhance care support through autonomous navigation, object manipulation, and natural language interaction, though challenges in privacy, ethics, and design persist.

ABSTRACT

Cooperation and collaboration robots, co-robots or cobots for short, are an integral part of factories. For example, they work closely with the fitters in the automotive sector, and everyone does what they do best. However, the novel robots are not only relevant in production and logistics, but also in the service sector, especially where proximity between them and the users is desired or unavoidable. For decades, individual solutions of a very different kind have been developed in care. Now experts are increasingly relying on co-robots and teaching them the special tasks that are involved in care or therapy. This article presents the advantages, but also the disadvantages of co-robots in care and support, and provides in-formation with regard to human-robot interaction and communication. The article is based on a model that has already been tested in various nursing and retirement homes, namely Lio from F&P Robotics, and uses results from accompanying studies. The authors can show that co-robots are ideal for care and support in many ways. Of course, it is also important to consider a few points in order to guarantee functionality and acceptance.

Motivation & Objective

• To assess the practical integration of co-robots like Lio in long-term care and rehabilitation environments.
• To identify the advantages and limitations of co-robots in human-robot interaction and communication within care contexts.
• To examine ethical and privacy concerns related to data collection via cameras and sensors in private care environments.
• To evaluate the role of co-robots in supporting physical care tasks such as feeding, mobility assistance, and hygiene.
• To provide design and implementation guidelines for co-robots in care based on empirical studies.

Proposed method

• The study uses Lio, a mobile co-robot with six degrees of freedom on a wheeled platform, equipped with cameras, microphones, laser and ultrasonic sensors for SLAM and obstacle avoidance.
• Lio employs facial and speech recognition, gesture recognition, and natural language processing for human-robot interaction.
• The robot features a modular end-effector system allowing attachment of grippers, vacuum tools, or massage heads.
• Two qualitative studies were conducted: one master thesis at the University of Basel (2017) and a usability study (2019) in nursing and rehabilitation facilities.
• Data were collected through observations, interviews, and user feedback in real-world care settings with patients, nurses, and caregivers.
• Ethical considerations were addressed through patient consent, data protection protocols, and the proposal of a patient decree to restrict robot use.

Experimental results

Research questions

• RQ1 How do co-robots like Lio perform in real-world care environments involving patients with varying care needs?
• RQ2 What are the key challenges in human-robot interaction, especially regarding communication, trust, and acceptance in care settings?
• RQ3 How do privacy and data protection concerns manifest when co-robots use cameras and microphones in semi-private care environments?
• RQ4 To what extent can co-robots assist with complex care tasks such as feeding, mobility support, and personal hygiene?
• RQ5 What design and ethical considerations are necessary to ensure the responsible deployment of co-robots in healthcare?

Key findings

• Lio successfully performed autonomous navigation, object transport, and interaction tasks such as greeting, object recognition, and voice-based control in real care environments.
• Patients and caregivers reported positive perceptions of Lio, particularly regarding its friendly appearance and ability to assist with routine tasks.
• The robot’s camera and microphone systems raised privacy concerns, especially regarding continuous data collection and potential misuse.
• The use of facial and speech recognition enabled personalized interaction but required careful data governance and informed consent.
• Two-armed co-robots like the prototype P-Care show potential for complex tasks such as feeding or assisting with hygiene, though no European studies on P-Care were conducted.
• Ethical and legal challenges related to informational autonomy and data protection were identified, necessitating patient-level consent mechanisms such as a patient decree.