arXiv subjects

Jens Gerken

Publications and source records attributed to Jens Gerken.

At least 19 recordsLinked to original sources

arXiv2026

A Roadmap of Mixed Reality Body Doubling for Adults with ADHD

Adults with ADHD may use a self-management technique known as Body Doubling, in which the participant employs the presence of one or more agents as a means of initiating and completing tasks. We developed a framework on body doubling with twelve dimensions to better understand the characteristics of body doubling and discover future research directions for developing and testing body doubling for adults with ADHD. Our framework accounts for individual motivation, agent-related dimensions, interaction related dimensions, contextual dimensions, and efficacy. These dimensions show existing research gaps such as limited mixed reality prototypes, possibilities for more interactive body doubles, and the need for empirical studies to further understand of body doubling and adults with ADHD.

cs.HC↗

arXiv2026

Robotic Affection -- Opportunities of AI-based haptic interactions to improve social robotic touch through a multi-deep-learning approach

Despite the advancement in robotic grasping and dexterity through haptic information, affective social touch, such as handshaking or reassuring stroking, remains a major challenge in Human-Robot-Interaction. This position paper examines current progress and limitations across artificial intelligence, haptics and robotics research, and proposes a novel multi-model architecture to address these gaps. Drawing inspiration from neurobiology, we decompose affective touch into distinct, specialized subtasks models. By treating affective touch as a distributed, closed-loop perceptual task rather than a monolithic motoric movement, we aim to overcome the "haptic uncanny valley" through a peer-to-peer, state-sharing framework. Our approach supports scalable and cumulative development within a Sim-to-Real pipeline, fostering interdisciplinary collaboration. By enabling haptics, AI, and robotics researchers to contribute independently yet coherently, we outline a pathway toward a unified, expressive system for social robotics.

cs.HC↗

arXiv2026

Preliminary Results of a Scoping Review on Assistive Technologies for Adults with ADHD

Attention Deficit Hyperactivity Disorder (ADHD), characterized by inattention, hyperactivity, and impulsivity, is prevalent in the adult population. Long perceived and treated as a childhood condition, ADHD and its characteristics nonetheless impact a significant portion of adults today. In contrast to children with ADHD, adults with ADHD face unique challenges in the workplace and in higher education. In this work-in-progress paper, we present a scoping review as a foundation to understand and explore existing technology-based approaches to support adults with ADHD. In total, our search returned 3,538 papers upon which we selected, based on PRISMA-ScR, a total of 46 papers for in-depth analysis. Our initial findings highlight that most papers take on a therapeutic or intervention perspective instead of a more positive support perspective. Our analysis also found a tremendous increase in recent papers on the topic, which highlights that more and more researchers are becoming aware of the need to address ADHD with adults. For the future, we aim to further analyze the corpus and identify research gaps and potentials for further development of ADHD assistive technologies.

cs.HC↗

arXiv2025

Challenges in Mixed Reality in Assisting Adults with ADHD Symptoms

In this position paper, we discuss symptoms of attention deficit hyperactivity disorder (ADHD) in adults, as well as available forms of treatment or assistance in the context of mixed reality. Mixed reality offers many potentials for assisting adults with symptoms commonly found in (but not limited to) ADHD, but the availability of mixed reality solutions is not only limited commercially, but also limited in terms of proof-of-concept prototypes. We discuss two major challenges with attention assistance using mixed reality solutions: the limited availability of adult-specific prototypes and studies, as well as the limited number of solutions that offer continuous intervention of ADHD-like symptoms that users can employ in their daily life.

cs.HC↗

arXiv2025

NoticeLight: Embracing Socio-Technical Asymmetry through Tangible Peripheral Robotic Embodiment in Hybrid Collaboration

Hybrid collaboration has become a fixture in modern workplaces, yet it introduces persistent socio-technical asymmetries-especially disadvantaging remote participants, who struggle with presence disparity, reduced visibility, and limited non-verbal communication. Traditional solutions often seek to erase these asymmetries, but recent research suggests embracing them as productive design constraints. In this context, we introduce NoticeLight: a tangible, peripheral robotic embodiment designed to augment hybrid meetings. NoticeLight transforms remote participants' digital presence into ambient, physical signals -- such as mood dynamics, verbal contribution mosaics, and attention cues -- within the co-located space. By abstracting group states into subtle light patterns, NoticeLight fosters peripheral awareness and balanced participation without disrupting meeting flow or demanding cognitive overload. This approach aligns with emerging perspectives in human-robot synergy, positioning robots as mediators that reshape, rather than replicate, human presence. Our work thereby advances the discourse on how robotic embodiments can empower equitable, dynamic collaboration in the workplace.

cs.HC↗

arXiv2024

Evaluating Assistive Technologies on a Trade Fair: Methodological Overview and Lessons Learned

User-centered evaluations are a core requirement in the development of new user related technologies. However, it is often difficult to recruit sufficient participants, especially if the target population is small, particularly busy, or in some way restricted in their mobility. We bypassed these problems by conducting studies on trade fairs that were specifically designed for our target population (potentially care-receiving individuals in wheelchairs) and therefore provided our users with external incentive to attend our study. This paper presents our gathered experiences, including methodological specifications and lessons learned, and is aimed to guide other researchers with conducting similar studies. In addition, we also discuss chances generated by this unconventional study environment as well as its limitations.

cs.HC↗

arXiv2024

Adaptive Control in Assistive Application -- A Study Evaluating Shared Control by Users with Limited Upper Limb Mobility

Shared control in assistive robotics blends human autonomy with computer assistance, thus simplifying complex tasks for individuals with physical impairments. This study assesses an adaptive Degrees of Freedom control method specifically tailored for individuals with upper limb impairments. It employs a between-subjects analysis with 24 participants, conducting 81 trials across three distinct input devices in a realistic everyday-task setting. Given the diverse capabilities of the vulnerable target demographic and the known challenges in statistical comparisons due to individual differences, the study focuses primarily on subjective qualitative data. The results reveal consistently high success rates in trial completions, irrespective of the input device used. Participants appreciated their involvement in the research process, displayed a positive outlook, and quick adaptability to the control system. Notably, each participant effectively managed the given task within a short time frame.

cs.HC↗

arXiv2024

AdaptiX -- A Transitional XR Framework for Development and Evaluation of Shared Control Applications in Assistive Robotics

With the ongoing efforts to empower people with mobility impairments and the increase in technological acceptance by the general public, assistive technologies, such as collaborative robotic arms, are gaining popularity. Yet, their widespread success is limited by usability issues, specifically the disparity between user input and software control along the autonomy continuum. To address this, shared control concepts provide opportunities to combine the targeted increase of user autonomy with a certain level of computer assistance. This paper presents the free and open-source AdaptiX XR framework for developing and evaluating shared control applications in a high-resolution simulation environment. The initial framework consists of a simulated robotic arm with an example scenario in Virtual Reality (VR), multiple standard control interfaces, and a specialized recording/replay system. AdaptiX can easily be extended for specific research needs, allowing Human-Robot Interaction (HRI) researchers to rapidly design and test novel interaction methods, intervention strategies, and multi-modal feedback techniques, without requiring an actual physical robotic arm during the early phases of ideation, prototyping, and evaluation. Also, a Robot Operating System (ROS) integration enables the controlling of a real robotic arm in a PhysicalTwin approach without any simulation-reality gap. Here, we review the capabilities and limitations of AdaptiX in detail and present three bodies of research based on the framework. AdaptiX can be accessed at https://adaptix.robot-research.de.

cs.HC↗

arXiv2024

Exploring Large Language Models to Facilitate Variable Autonomy for Human-Robot Teaming

In a rapidly evolving digital landscape autonomous tools and robots are becoming commonplace. Recognizing the significance of this development, this paper explores the integration of Large Language Models (LLMs) like Generative pre-trained transformer (GPT) into human-robot teaming environments to facilitate variable autonomy through the means of verbal human-robot communication. In this paper, we introduce a novel framework for such a GPT-powered multi-robot testbed environment, based on a Unity Virtual Reality (VR) setting. This system allows users to interact with robot agents through natural language, each powered by individual GPT cores. By means of OpenAI's function calling, we bridge the gap between unstructured natural language input and structure robot actions. A user study with 12 participants explores the effectiveness of GPT-4 and, more importantly, user strategies when being given the opportunity to converse in natural language within a multi-robot environment. Our findings suggest that users may have preconceived expectations on how to converse with robots and seldom try to explore the actual language and cognitive capabilities of their robot collaborators. Still, those users who did explore where able to benefit from a much more natural flow of communication and human-like back-and-forth. We provide a set of lessons learned for future research and technical implementations of similar systems.

cs.HC↗

arXiv2024

Multiple Ways of Working with Users to Develop Physically Assistive Robots

Despite the growth of physically assistive robotics (PAR) research over the last decade, nearly half of PAR user studies do not involve participants with the target disabilities. There are several reasons for this -- recruitment challenges, small sample sizes, and transportation logistics -- all influenced by systemic barriers that people with disabilities face. However, it is well-established that working with end-users results in technology that better addresses their needs and integrates with their lived circumstances. In this paper, we reflect on multiple approaches we have taken to working with people with motor impairments across the design, development, and evaluation of three PAR projects: (a) assistive feeding with a robot arm; (b) assistive teleoperation with a mobile manipulator; and (c) shared control with a robot arm. We discuss these approaches to working with users along three dimensions -- individual vs. community-level insight, logistic burden on end-users vs. researchers, and benefit to researchers vs. community -- and share recommendations for how other PAR researchers can incorporate users into their work.

cs.HC↗

arXiv2024

Hands-On Robotics: Enabling Communication Through Direct Gesture Control

Effective Human-Robot Interaction (HRI) is fundamental to seamlessly integrating robotic systems into our daily lives. However, current communication modes require additional technological interfaces, which can be cumbersome and indirect. This paper presents a novel approach, using direct motion-based communication by moving a robot's end effector. Our strategy enables users to communicate with a robot by using four distinct gestures -- two handshakes ('formal' and 'informal') and two letters ('W' and 'S'). As a proof-of-concept, we conducted a user study with 16 participants, capturing subjective experience ratings and objective data for training machine learning classifiers. Our findings show that the four different gestures performed by moving the robot's end effector can be distinguished with close to 100% accuracy. Our research offers implications for the design of future HRI interfaces, suggesting that motion-based interaction can empower human operators to communicate directly with robots, removing the necessity for additional hardware.

cs.HC↗

arXiv2024

Exploring of Discrete and Continuous Input Control for AI-enhanced Assistive Robotic Arms

Robotic arms, integral in domestic care for individuals with motor impairments, enable them to perform Activities of Daily Living (ADLs) independently, reducing dependence on human caregivers. These collaborative robots require users to manage multiple Degrees-of-Freedom (DoFs) for tasks like grasping and manipulating objects. Conventional input devices, typically limited to two DoFs, necessitate frequent and complex mode switches to control individual DoFs. Modern adaptive controls with feed-forward multi-modal feedback reduce the overall task completion time, number of mode switches, and cognitive load. Despite the variety of input devices available, their effectiveness in adaptive settings with assistive robotics has yet to be thoroughly assessed. This study explores three different input devices by integrating them into an established XR framework for assistive robotics, evaluating them and providing empirical insights through a preliminary study for future developments.

cs.HC↗

arXiv2024

Trickery: Exploring a Serious Game Approach to Raise Awareness of Deceptive Patterns

Deceptive patterns are often used in interface design to manipulate users into taking actions they would not otherwise take, such as consenting to excessive data collection. We present Trickery, a narrative serious game that incorporates seven gamified deceptive patterns. We designed the game as a potential mechanism for raising awareness of, and increasing resistance to, deceptive patterns through direct consequences of player actions. We conducted an explorative gameplay study to examine player behavior when confronted with the game Trickery. In addition, we conducted an online survey to shed light on the perceived helpfulness of our gamified deceptive patterns. Our results reveal different player motivations and driving forces that players used to justify their behavior when confronted with deceptive patterns in the Trickery game. In addition, we identified several influencing factors that need to be considered when adapting deceptive patterns into gameplay. Overall, the approach appears to be a promising solution for increasing user understanding and awareness of deceptive patterns.

cs.HC↗

arXiv2023

In Time and Space: Towards Usable Adaptive Control for Assistive Robotic Arms

Robotic solutions, in particular robotic arms, are becoming more frequently deployed for close collaboration with humans, for example in manufacturing or domestic care environments. These robotic arms require the user to control several Degrees-of-Freedom (DoFs) to perform tasks, primarily involving grasping and manipulating objects. Standard input devices predominantly have two DoFs, requiring time-consuming and cognitively demanding mode switches to select individual DoFs. Contemporary Adaptive DoF Mapping Controls (ADMCs) have shown to decrease the necessary number of mode switches but were up to now not able to significantly reduce the perceived workload. Users still bear the mental workload of incorporating abstract mode switching into their workflow. We address this by providing feed-forward multimodal feedback using updated recommendations of ADMC, allowing users to visually compare the current and the suggested mapping in real-time. We contrast the effectiveness of two new approaches that a) continuously recommend updated DoF combinations or b) use discrete thresholds between current robot movements and new recommendations. Both are compared in a Virtual Reality (VR) in-person study against a classic control method. Significant results for lowered task completion time, fewer mode switches, and reduced perceived workload conclusively establish that in combination with feedforward, ADMC methods can indeed outperform classic mode switching. A lack of apparent quantitative differences between Continuous and Threshold reveals the importance of user-centered customization options. Including these implications in the development process will improve usability, which is essential for successfully implementing robotic technologies with high user acceptance.

cs.HC↗

arXiv2023

How to Communicate Robot Motion Intent: A Scoping Review

Robots are becoming increasingly omnipresent in our daily lives, supporting us and carrying out autonomous tasks. In Human-Robot Interaction, human actors benefit from understanding the robot's motion intent to avoid task failures and foster collaboration. Finding effective ways to communicate this intent to users has recently received increased research interest. However, no common language has been established to systematize robot motion intent. This work presents a scoping review aimed at unifying existing knowledge. Based on our analysis, we present an intent communication model that depicts the relationship between robot and human through different intent dimensions (intent type, intent information, intent location). We discuss these different intent dimensions and their interrelationships with different kinds of robots and human roles. Throughout our analysis, we classify the existing research literature along our intent communication model, allowing us to identify key patterns and possible directions for future research.

cs.HC↗

arXiv2023

Extending Cobot's Motion Intention Visualization by Haptic Feedback

Nowadays, robots are found in a growing number of areas where they collaborate closely with humans. Enabled by lightweight materials and safety sensors, these cobots are gaining increasing popularity in domestic care, supporting people with physical impairments in their everyday lives. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior, which is crucial for achieving trust and user acceptance. One significant aspect of predicting cobot behavior is understanding their motion intention and comprehending how they "think" about their actions. Moreover, other information sources often occupy human visual and audio modalities, rendering them frequently unsuitable for transmitting such information. We work on a solution that communicates cobot intention via haptic feedback to tackle this challenge. In our concept, we map planned motions of the cobot to different haptic patterns to extend the visual intention feedback.

cs.HC↗

arXiv2023

Exploring AI-enhanced Shared Control for an Assistive Robotic Arm

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, such as the Kinova Jaco robotic arm. However, they mostly require complex manual control, which can overwhelm users. As a result, researchers have explored ways to let such robots act autonomously. However, at least for this specific group of users, such an approach has shown to be futile. Here, users want to stay in control to achieve a higher level of personal autonomy, to which an autonomous robot runs counter. In our research, we explore how Artifical Intelligence (AI) can be integrated into a shared control paradigm. In particular, we focus on the consequential requirements for the interface between human and robot and how we can keep humans in the loop while still significantly reducing the mental load and required motor skills.

cs.HC↗

arXiv2023

HaptiX: Vibrotactile Haptic Feedback for Communication of 3D Directional Cues

In Human-Computer-Interaction, vibrotactile haptic feedback offers the advantage of being independent of any visual perception of the environment. Most importantly, the user's field of view is not obscured by user interface elements, and the visual sense is not unnecessarily strained. This is especially advantageous when the visual channel is already busy, or the visual sense is limited. We developed three design variants based on different vibrotactile illusions to communicate 3D directional cues. In particular, we explored two variants based on the vibrotactile illusion of the cutaneous rabbit and one based on apparent vibrotactile motion. To communicate gradient information, we combined these with pulse-based and intensity-based mapping. A subsequent study showed that the pulse-based variants based on the vibrotactile illusion of the cutaneous rabbit are suitable for communicating both directional and gradient characteristics. The results further show that a representation of 3D directions via vibrations can be effective and beneficial.

cs.HC↗