Browsing by Author "Kuchenbecker, Katherine J. (Hon.-Prof. Dr.)"

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Open Access
Capturing and recognizing multimodal surface interactions as embedded high-dimensional distributions
(2025) Khojasteh, Behnam; Kuchenbecker, Katherine J. (Hon.-Prof. Dr.)
Exploring a surface with a handheld tool generates complex contact signals that uniquely encode the surface’s properties - a needle hidden in a haystack of data. Humans naturally integrate visual, auditory, and haptic sensory data during these interactions to accurately assess and recognize surfaces. However, enabling artificial systems to perceive and recognize surfaces with human-like proficiency remains a significant challenge. The complexity and dimensionality of multi-modal sensor data, particularly in the intricate and dynamic modality of touch, hinders effective sensing and processing. Successfully overcoming these challenges will open up new possibilities in applications such as quality control, material documentation, and robotics. This dissertation addresses these issues at the levels of both the sensing hardware and the processing algorithms by introducing an automated similarity framework for multimodal surface recognition, developing a haptic-auditory test bed for acquiring high-quality surface data, and exploring optimal sensing configurations to improve recognition performance and robustness.
Open Access
Engineering and evaluating naturalistic vibrotactile feedback for telerobotic assembly
(2024) Gong, Yijie; Kuchenbecker, Katherine J. (Hon.-Prof. Dr.)
Teleoperation allows workers on a construction site to assemble pre-fabricated building components by controlling powerful machines from a safe distance. However, teleoperation's primary reliance on visual feedback limits the operator's efficiency in situations with stiff contact or poor visibility, compromising their situational awareness and thus increasing the difficulty of the task; it also makes construction machines more difficult to learn to operate. To bridge this gap, we propose that reliable, economical, and easy-to-implement naturalistic vibrotactile feedback could improve telerobotic control interfaces in construction and other application areas such as surgery. This type of feedback enables the operator to feel the natural vibrations experienced by the robot, which contain crucial information about its motions and its physical interactions with the environment. This dissertation explores how to deliver naturalistic vibrotactile feedback from a robot's end-effector to the hand of an operator performing telerobotic assembly tasks; furthermore, it seeks to understand the effects of such haptic cues. The presented research can be divided into four parts. We first describe the engineering of AiroTouch, a naturalistic vibrotactile feedback system tailored for use on construction sites but suitable for many other applications of telerobotics. Then we evaluate AiroTouch and explore the effects of the naturalistic vibrotactile feedback it delivers in three user studies conducted either in laboratory settings or on a construction site. The primary contribution of this dissertation is the clear explanation of details that are essential for the effective implementation of naturalistic vibrotactile feedback. We demonstrate that our accessible, audio-based approach can enhance user performance and experience during telerobotic assembly in construction and other application domains. These findings lay the foundation for further exploration of the potential benefits of incorporating haptic cues to enhance user experience during teleoperation.