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Speech command recognition (SCR) has been commonly used on resource constrained devices to achieve hands-free user experience. However, in real applications, confusion among commands with similar pronunciations often happens due to the…
Suction cups offer a useful gripping solution, particularly in industrial robotics and warehouse applications. Vision-based grasp algorithms, like Dex-Net, show promise but struggle to accurately perceive dark or reflective objects,…
Secure Device Pairing (SDP) relies on an out-of-band channel to authenticate devices. This requires a common hardware interface, which limits the use of existing SDP systems. We propose to use short-range acoustic communication for the…
The objective of this paper is to describe the study on speech interaction mode for home automation control of equipment by impaired people for an inclusive housing. The study is related to the HIP HOPE project concerning a building of 19…
Advances in eye-tracking control for assistive robotic arms provide intuitive interaction opportunities for people with physical disabilities. Shared control has gained interest in recent years by improving user satisfaction through partial…
In recent years, the integration of additive manufacturing (AM) and industrial robotics has opened new perspectives for the production of complex components, particularly in the automotive sector. Robot-assisted additive manufacturing…
How can we train an assistive human-machine interface (e.g., an electromyography-based limb prosthesis) to translate a user's raw command signals into the actions of a robot or computer when there is no prior mapping, we cannot ask the user…
Users of assistive devices vary in their extent of motor impairment, and hence their physical interaction with control interfaces can differ. There is the potential for improved utility if control interface actuation is mapped to assistive…
In the upcoming industrial internet of things (IIoT) era, a surge of task-oriented applications will rely on real-time wireless control systems (WCSs). For these systems, ultra-reliable and low-latency wireless communication will be crucial…
Adaptive interventions (AIs) are increasingly becoming popular in medical and behavioral sciences. An AI is a sequence of individualized intervention options that specify for whom and under what conditions different intervention options…
This paper presents a hetero-associative sequential memory system for mobile manipulators that learns compact, neuromorphic bindings between robot joint states and tactile observations to produce step-wise action decisions with low compute…
Collaborative robots became a popular tool for increasing productivity in partly automated manufacturing plants. Intuitive robot teaching methods are required to quickly and flexibly adapt the robot programs to new tasks. Gestures have an…
The construction of preamble sequences for channel estimation by superposition of orthogonal pilots can improve performance of massive grant-free uplink from machine-type devices. In this letter, a technique is proposed to obtain full…
When humans control drones, cars, and robots, we often have some preconceived notion of how our inputs should make the system behave. Existing approaches to teleoperation typically assume a one-size-fits-all approach, where the designers…
Assistive machines endow people with limited mobility the opportunity to live more independently. However, operating these machines poses risks to the safety of the human operator as well as the surrounding environment. Thus, proper user…
In this paper, we study a sequential decision-making problem, called Adaptive Sampling for Discovery (ASD). Starting with a large unlabeled dataset, algorithms for ASD adaptively label the points with the goal to maximize the sum of…
Assistive technologies and in particular assistive robotic arms have the potential to enable people with motor impairments to live a self-determined life. More and more of these systems have become available for end users in recent years,…
Grasping an unknown object is difficult for robot hands. When the characteristics of the object are unknown, knowing how to plan the speed at and width to which the fingers are narrowed is difficult. In this paper, we propose a method to…
The increasing scale and complexity of large language models (LLMs) pose significant inference latency challenges, primarily due to their autoregressive decoding paradigm characterized by the sequential nature of next-token prediction. By…
Efficient data collection from a multitude of Internet of Things (IoT) devices is crucial for various applications, yet existing solutions often struggle with minimizing access delay and Age of Information (AoI), especially when managing…