Towards Privacy-Aware and Personalised Assistive Robots: A User-Centred Approach

• URL: http://arxiv.org/abs/2405.14528v1
• Date: Thu, 23 May 2024 13:14:08 GMT
• Title: Towards Privacy-Aware and Personalised Assistive Robots: A User-Centred Approach
• Authors: Fernando E. Casado,
• Abstract summary: This research pioneers user-centric, privacy-aware technologies such as Federated Learning (FL) FL enables collaborative learning without sharing sensitive data, addressing privacy and scalability issues. This work includes developing solutions for smart wheelchair assistance, enhancing user independence and well-being.
• Score: 55.5769013369398
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The global increase in the elderly population necessitates innovative long-term care solutions to improve the quality of life for vulnerable individuals while reducing caregiver burdens. Assistive robots, leveraging advancements in Machine Learning, offer promising personalised support. However, their integration into daily life raises significant privacy concerns. Widely used frameworks like the Robot Operating System (ROS) historically lack inherent privacy mechanisms, complicating data-driven approaches in robotics. This research pioneers user-centric, privacy-aware technologies such as Federated Learning (FL) to advance assistive robotics. FL enables collaborative learning without sharing sensitive data, addressing privacy and scalability issues. This work includes developing solutions for smart wheelchair assistance, enhancing user independence and well-being. By tackling challenges related to non-stationary data and heterogeneous environments, the research aims to improve personalisation and user experience. Ultimately, it seeks to lead the responsible integration of assistive robots into society, enhancing the quality of life for elderly and care-dependent individuals.

Related papers

• A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics [53.33976793493801]
  We organized the Robot Air Hockey Challenge at the NeurIPS 2023 conference. We focus on practical challenges in robotics, such as the sim-to-real gap, low-level control issues, safety problems, real-time requirements, and the limited availability of real-world data. Results show that solutions combining learning-based approaches with prior knowledge outperform those relying solely on data when real-world deployment is challenging.
  arXiv  Detail & Related papers  (2024-11-08T17:20:47Z)
• Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models [81.55156507635286]
  Legged robots are physically capable of navigating a diverse variety of environments and overcoming a wide range of obstructions. Current learning methods often struggle with generalization to the long tail of unexpected situations without heavy human supervision. We propose a system, VLM-Predictive Control (VLM-PC), combining two key components that we find to be crucial for eliciting on-the-fly, adaptive behavior selection.
  arXiv  Detail & Related papers  (2024-07-02T21:00:30Z)
• Smart Help: Strategic Opponent Modeling for Proactive and Adaptive Robot Assistance in Households [30.33911147366425]
  Smart Help aims to provide proactive yet adaptive support to human agents with diverse disabilities. We introduce an innovative opponent modeling module that provides a nuanced understanding of the main agent's capabilities and goals. Our findings illustrate the potential of AI-imbued assistive robots in improving the well-being of vulnerable groups.
  arXiv  Detail & Related papers  (2024-04-13T13:03:59Z)
• Socially Pertinent Robots in Gerontological Healthcare [78.35311825198136]
  This paper is an attempt to partially answer the question, via two waves of experiments with patients and companions in a day-care gerontological facility in Paris with a full-sized humanoid robot endowed with social and conversational interaction capabilities. Overall, the users are receptive to this technology, especially when the robot perception and action skills are robust to environmental clutter and flexible to handle a plethora of different interactions.
  arXiv  Detail & Related papers  (2024-04-11T08:43:37Z)
• Perceptions of Humanoid Robots in Caregiving: A Study of Skilled Nursing Home and Long Term Care Administrators [0.0]
  Authors surveyed nursing homes executives to understand their perspectives on the use of humanoid robots in their facilities. Results revealed that the executives were keen on exploring other avenues for care such as robotics. While acknowledging benefits like improved engagement and staff support, concerns persist about costs, impacts on human interaction, and doubts about robot effectiveness.
  arXiv  Detail & Related papers  (2024-01-04T07:26:52Z)
• Model Predictive Control for Fluid Human-to-Robot Handovers [50.72520769938633]
  Planning motions that take human comfort into account is not a part of the human-robot handover process. We propose to generate smooth motions via an efficient model-predictive control framework. We conduct human-to-robot handover experiments on a diverse set of objects with several users.
  arXiv  Detail & Related papers  (2022-03-31T23:08:20Z)
• Federated Continual Learning for Socially Aware Robotics [4.224305864052757]
  Social robots do not adapt their behavior to new users, and they do not provide sufficient privacy protections. We propose a decentralized learning alternative that improves the privacy and personalization of social robots. We show that decentralized learning is a viable alternative to centralized learning in a proof-of-concept Socially-Aware Navigation domain.
  arXiv  Detail & Related papers  (2022-01-14T15:54:51Z)
• Marvin: Innovative Omni-Directional Robotic Assistant for Domestic Environments [0.0]
  We present Marvin, a novel assistive robot we developed with a modular layer-based architecture. We propose an omnidirectional platform provided with four mecanum wheels, which enable autonomous navigation. Deep learning solutions for visual perception, person pose classification and vocal command completely run on the embedded hardware of the robot.
  arXiv  Detail & Related papers  (2021-12-10T15:27:53Z)
• Framework for A Personalized Intelligent Assistant to Elderly People for Activities of Daily Living [0.0]
  This work proposes a framework for development of a Personalized Intelligent Assistant to help elderly people perform Activities of Daily Living. This framework can analyze different tasks performed by the user and recommend activities by considering their daily routine, current affective state and the underlining user experience. The results presented show that the model achieves a performance accuracy of 73.12% when modelling a specific user.
  arXiv  Detail & Related papers  (2021-06-29T17:36:07Z)
• Cognitive architecture aided by working-memory for self-supervised multi-modal humans recognition [54.749127627191655]
  The ability to recognize human partners is an important social skill to build personalized and long-term human-robot interactions. Deep learning networks have achieved state-of-the-art results and demonstrated to be suitable tools to address such a task. One solution is to make robots learn from their first-hand sensory data with self-supervision.
  arXiv  Detail & Related papers  (2021-03-16T13:50:24Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.