Related papers: Adaptive Multimodal Music Learning via Interactive…
The recent development of novel aerial vehicles capable of physically interacting with the environment leads to new applications such as contact-based inspection. These tasks require the robotic system to exchange forces with…
Designing adaptive tutoring systems for software learning presents challenges in determining appropriate instructional modalities. To inform the design of such systems, we conducted an observational study of ten human teacher-student pairs…
This paper outlines the development and evaluation of a wearable haptic game interface. The device differs from many traditional haptic feedback implementation in that it combines vibrotactile feedback with gesture based input, thus…
The replication of object stiffness is essential for enhancing haptic feedback in virtual environments. However, existing research has overlooked how stylus stiffness influences the perception of virtual object stiffness during…
Inspired by widely used soft fingers on grasping, we propose a method of rigid-soft interactive learning, aiming at reducing the time of data collection. In this paper, we classify the interaction categories into Rigid-Rigid, Rigid-Soft,…
Robust and generalized tool manipulation requires an understanding of the properties and affordances of different tools. We investigate whether linguistic information about a tool (e.g., its geometry, common uses) can help control policies…
This paper brings into discussion some of the most relevant technological challenges involving haptic systems in medical education. One of these challenges is choosing the suitable haptic hardware, API or framework for developing a…
The growing ubiquity of artificial intelligence (AI), in particular large language models (LLMs), has profoundly altered the way in which learners gain knowledge and interact with learning material, with many claiming that AI positively…
Multimodal continual instruction tuning enables multimodal large language models to sequentially adapt to new tasks while building upon previously acquired knowledge. However, this continual learning paradigm faces the significant challenge…
Contact-rich manipulation tasks such as precision assembly require precise control of interaction forces, yet existing imitation learning methods rely mainly on vision-only demonstrations. We propose ManipForce, a handheld system designed…
We have recently seen great progress in learning interpretable music representations, ranging from basic factors, such as pitch and timbre, to high-level concepts, such as chord and texture. However, most methods rely heavily on music…
A major challenge in the field of education is providing review schedules that present learned items at appropriate intervals to each student so that memory is retained over time. In recent years, attempts have been made to formulate item…
Haptic perception and feedback play a pivotal role in interactive experiences, forming an essential component of human-computer interaction (HCI). In recent years, the field of haptic interaction has witnessed significant advancements,…
Deep multimodal learning has achieved great progress in recent years. However, current fusion approaches are static in nature, i.e., they process and fuse multimodal inputs with identical computation, without accounting for diverse…
Recent years have witnessed many successful trials in the robot learning field. For contact-rich robotic tasks, it is challenging to learn coordinated motor skills by reinforcement learning. Imitation learning solves this problem by using a…
Learning to lift and rotate objects with the fingertips is necessary for autonomous in-hand dexterous manipulation. In our study, we explore the impact of various factors on successful learning strategies for this task. Specifically, we…
Imitation learning aims to mimic the behavior of experts without explicit reward signals. Passive imitation learning methods which use static expert datasets typically suffer from compounding error, low sample efficiency, and high…
The provision of robotic assistance during motor training has proven to be effective in enhancing motor learning in some healthy trainee groups as well as patients. Personalizing such robotic assistance can help further improve motor…
Instructors play a pivotal role in integrating AI into education, yet their adoption of AI-powered tools remains inconsistent. Despite this, limited research explores how to design AI tools that support broader instructor adoption. This…
The absence of physical interfaces creates challenges when interacting with touchscreen technology. This study aims to investigate an innovative haptic solution for interacting with graphical user interfaces. A motorized shape-changing…