Enhancing Object Search in Indoor Spaces via Personalized Object-factored Ontologies

TL;DR

This paper introduces a novel framework for personalized object-factored ontologies and adaptive inferencing to improve long-term object search capabilities of service robots in indoor environments.

Contribution

It presents a new approach combining personalized ontologies and adaptive inferencing, enhancing multi-object search performance in indoor environments.

Findings

Improved object search accuracy in real environments.

Personalization enhances state-of-the-art methods.

Adaptive inferencing boosts long-term search efficiency.

Abstract

Personalization is critical for the advancement of service robots. Robots need to develop tailored understandings of the environments they are put in. Moreover, they need to be aware of changes in the environment to facilitate long-term deployment. Long-term understanding as well as personalization is necessary to execute complex tasks like prepare dinner table or tidy my room. A precursor to such tasks is that of Object Search. Consequently, this paper focuses on locating and searching multiple objects in indoor environments. In this paper, we propose two crucial novelties. Firstly, we propose a novel framework that can enable robots to deduce Personalized Ontologies of indoor environments. Our framework consists of a personalization schema that enables the robot to tune its understanding of ontologies. Secondly, we propose an Adaptive Inferencing strategy. We integrate Dynamic Belief Updates into our approach which improves performance in multi-object search tasks. The cumulative effect of personalization and adaptive inferencing is an improved capability in long-term object search. This framework is implemented on top of a multi-layered semantic map. We conduct experiments in real environments and compare our results against various state-of-the-art (SOTA) methods to demonstrate the effectiveness of our approach. Additionally, we show that personalization can act as a catalyst to enhance the performance of SOTAs. Video Link: https://bit.ly/3WHk9i9