Intention prediction approach to interact naturally with the microworld

Abstract

Micromanipulation tools are not yet commonly used in the industry or in the research due to the lack of natural and intuitive human-computer interfaces. This work proposes a vision based approach using a Kinect RGB-Depth sensor to provide a "metaphor-free" interface. An intention prediction approach is proposed, based on a cognitive science computational model, to allow a more natural interaction without any prior instructions. This model is compared to a vision based gesture recognition approach in terms of naturalness and intuitiveness. It shows an improvement in user performance in terms of duration and success of the task, and a qualitative preference for the proposed approach evaluated by a user survey.

Usability and user experience evaluation of natural user interfaces: a systematic mapping study

“…The extraction strategy certifies the application of the same data extraction criteria for all papers selected, facilitating the classification. The 56 selected publications are [23–78 ].…”

Multimodal Learning‐Based Proactive Human Handover Intention Prediction Using Wearable Data Gloves and Augmented Reality

“…In terms of research on human handover intention prediction, Tanaka et al proposed a motion planner tailored for human–robot handover applications, developing a method for forecasting human action trajectories within discrete workspaces using the Markov model. [ 28 ] Cohen et al [ 29 ] used the Kinect camera to establish a “metaphor‐free” interface and then introduced a technique for predicting human intentions based on a computational cognitive science framework. Song et al [ 30 ] devised a visual framework based on probability to anticipate human intentions in the context of human–object interactions using visual frames.…”