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Steven M. LaValle

Publications and source records attributed to Steven M. LaValle.

At least 37 records · Page 2Linked to original sources

Virtual Reality Sickness Reduces Attention During Immersive Experiences

In this paper, we show that Virtual Reality (VR) sickness is associated with a reduction in attention, which was detected with the P3b Event-Related Potential (ERP) component from electroencephalography (EEG) measurements collected in a dual-task paradigm. We hypothesized that sickness symptoms such as nausea, eyestrain, and fatigue would reduce the users' capacity to pay attention to tasks completed in a virtual environment, and that this reduction in attention would be dynamically reflected in a decrease of the P3b amplitude while VR sickness was experienced. In a user study, participants were taken on a tour through a museum in VR along paths with varying amounts of rotation, shown previously to cause different levels of VR sickness. While paying attention to the virtual museum (the primary task), participants were asked to silently count tones of a different frequency (the secondary task). Control measurements for comparison against the VR sickness conditions were taken when the users were not wearing the Head-Mounted Display (HMD) and while they were immersed in VR but not moving through the environment. This exploratory study shows, across multiple analyses, that the effect mean amplitude of the P3b collected during the task is associated with both sickness severity measured after the task with a questionnaire (SSQ) and with the number of counting errors on the secondary task. Thus, VR sickness may impair attention and task performance, and these changes in attention can be tracked with ERP measures as they happen, without asking participants to assess their sickness symptoms in the moment.

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A Mathematical Characterization of Minimally Sufficient Robot Brains

This paper addresses the lower limits of encoding and processing the information acquired through interactions between an internal system (robot algorithms or software) and an external system (robot body and its environment) in terms of action and observation histories. Both are modeled as transition systems. We want to know the weakest internal system that is sufficient for achieving passive (filtering) and active (planning) tasks. We introduce the notion of an information transition system for the internal system which is a transition system over a space of information states that reflect a robot's or other observer's perspective based on limited sensing, memory, computation, and actuation. An information transition system is viewed as a filter and a policy or plan is viewed as a function that labels the states of this information transition system. Regardless of whether internal systems are obtained by learning algorithms, planning algorithms, or human insight, we want to know the limits of feasibility for given robot hardware and tasks. We establish, in a general setting, that minimal information transition systems exist up to reasonable equivalence assumptions, and are unique under some general conditions. We then apply the theory to generate new insights into several problems, including optimal sensor fusion/filtering, solving basic planning tasks, and finding minimal representations for modeling a system given input-output relations.

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Bang-Bang Boosting of RRTs

This paper presents methods for dramatically improving the performance of sampling-based kinodynamic planners. The key component is the first-known complete, exact steering method that produces a time-optimal trajectory between any states for a vector of synchronized double integrators. This method is applied in three ways: 1) to generate RRT edges that quickly solve the two-point boundary-value problems, 2) to produce a (quasi)metric for more accurate Voronoi bias in RRTs, and 3) to iteratively time-optimize a given collision-free trajectory. Experiments are performed for state spaces with up to 2000 dimensions, resulting in improved computed trajectories and orders of magnitude computation time improvements over using ordinary metrics and constant controls.

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The Limits of Learning and Planning: Minimal Sufficient Information Transition Systems

In this paper, we view a policy or plan as a transition system over a space of information states that reflect a robot's or other observer's perspective based on limited sensing, memory, computation, and actuation. Regardless of whether policies are obtained by learning algorithms, planning algorithms, or human insight, we want to know the limits of feasibility for given robot hardware and tasks. Toward the quest to find the best policies, we establish in a general setting that minimal information transition systems (ITSs) exist up to reasonable equivalence assumptions, and are unique under some general conditions. We then apply the theory to generate new insights into several problems, including optimal sensor fusion/filtering, solving basic planning tasks, and finding minimal representations for feasible policies.

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Leaning-Based Control of an Immersive-Telepresence Robot

In this paper, we present an implementation of a leaning-based control of a differential drive telepresence robot and a user study in simulation, with the goal of bringing the same functionality to a real telepresence robot. The participants used a balance board to control the robot and viewed the virtual environment through a head-mounted display. The main motivation for using a balance board as the control device stems from Virtual Reality (VR) sickness; even small movements of your own body matching the motions seen on the screen decrease the sensory conflict between vision and vestibular organs, which lies at the heart of most theories regarding the onset of VR sickness. To test the hypothesis that the balance board as a control method would be less sickening than using joysticks, we designed a user study (N=32, 15 women) in which the participants drove a simulated differential drive robot in a virtual environment with either a Nintendo Wii Balance Board or joysticks. However, our pre-registered main hypotheses were not supported; the joystick did not cause any more VR sickness on the participants than the balance board, and the board proved to be statistically significantly more difficult to use, both subjectively and objectively. Analyzing the open-ended questions revealed these results to be likely connected, meaning that the difficulty of use seemed to affect sickness; even unlimited training time before the test did not make the use as easy as the familiar joystick. Thus, making the board easier to use is a key to enable its potential; we present a few possibilities towards this goal.

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Visibility-Inspired Models of Touch Sensors for Navigation

This paper introduces mathematical models of \sensors\ for mobile robots based on visibility. Serving a purpose similar to the pinhole camera model for computer vision, the introduced models are expected to provide a useful, idealized characterization of task-relevant information that can be inferred from their outputs or observations. Possible tasks include navigation, localization and mapping when a mobile robot is deployed in an unknown environment. These models allow direct comparisons to be made between traditional depth sensors, highlighting cases in which touch sensing may be interchangeable with time of flight or vision sensors, and characterizing unique advantages provided by touch sensing. The models include contact detection, compression, load bearing, and deflection. The results could serve as a basic building block for innovative touch sensor designs for mobile robot sensor fusion systems.

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HI-DWA: Human-Influenced Dynamic Window Approach for Shared Control of a Telepresence Robot

This paper considers the problem of enabling the user to modify the path of a telepresence robot. The robot is capable of autonomously navigating to a goal predefined by the user, but the user might still want to modify the path, for example, to go further away from other people, or to go closer to landmarks she wants to see on the way. We propose Human-Influenced Dynamic Window Approach (HI-DWA), a shared control method aimed for telepresence robots based on Dynamic Window Approach (DWA) that allows the user to influence the control input given to the robot. To verify the proposed method, we performed a user study (N=32) in Virtual Reality (VR) to compare HI-DWA with switching between autonomous navigation and manual control for controlling a simulated telepresence robot moving in a virtual environment. Results showed that users reached their goal faster using HI-DWA controller and found it easier to use. Preference between the two methods was split equally. Qualitative analysis revealed that a major reason for the participants that preferred switching between two modes was the feeling of control. We also analyzed the effect of different input methods, joystick and gesture, on the preference and perceived workload.

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The Body Scaling Effect and Its Impact on Physics Plausibility

In this study we investigated the effect of body ownership illusion-based body scaling on physics plausibility in Virtual Reality (VR). Our interest was in examining whether body ownership illusion-based body scaling could affect the plausibility of rigid body dynamics similarly to altering VR users' scale by manipulating their virtual interpupillary distance and viewpoint height. The procedure involved the conceptual replication of two previous studies. We investigated physics plausibility with 40 participants under two conditions. In our synchronous condition, we used visuo-tactile stimuli to elicit a body ownership illusion of inhabiting an invisible doll-sized body on participants reclining on an exam table. Our asynchronous condition was otherwise similar, but the visuo-tactile stimuli were provided asynchronously to prevent the onset of the body ownership illusion. We were interested in whether the correct approximation of physics (true physics) or physics that are incorrect and appearing as if the environment is five times larger instead (movie physics) appear more realistic to participants as a function of body scale. We found that movie physics did appear more realistic to participants under the body ownership illusion condition. However, our hypothesis that true physics would appear more realistic in the asynchronous condition was unsupported. Our exploratory analyses revealed that movie physics were perceived as plausible under both conditions. Moreover, we were not able to replicate previous findings from literature concerning object size estimations while inhabiting a small invisible body. However, we found a significant opposite effect regarding size estimations; the object sizes were on average underestimated during the synchronous visuo-tactile condition when compared to the asynchronous condition.

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An Enactivist-Inspired Mathematical Model of Cognition

We formulate five basic tenets of enactivist cognitive science that we have carefully identified in the relevant literature as the main underlying principles of that philosophy. We then develop a mathematical framework to talk about cognitive systems (both artificial and natural) which complies with these enactivist tenets. In particular we pay attention that our mathematical modeling does not attribute contentful symbolic representations to the agents, and that the agent's brain, body and environment are modeled in a way that makes them an inseparable part of a greater totality. The purpose is to create a mathematical foundation for cognition which is in line with enactivism. We see two main benefits of doing so: (1) It enables enactivist ideas to be more accessible for computer scientists, AI researchers, roboticists, cognitive scientists, and psychologists, and (2) it gives the philosophers a mathematical tool which can be used to clarify their notions and help with their debates. Our main notion is that of a sensorimotor system which is a special case of a well studied notion of a transition system. We also consider related notions such as labeled transition systems and deterministic automata. We analyze a notion called sufficiency and show that it is a very good candidate for a foundational notion in the "mathematics of cognition from an enactivist perspective". We demonstrate its importance by proving a uniqueness theorem about the minimal sufficient refinements (which correspond in some sense to an optimal attunement of an organism to its environment) and by showing that sufficiency corresponds to known notions such as sufficient history information spaces. We then develop other related notions such as degree of insufficiency, universal covers, hierarchies, strategic sufficiency. In the end, we tie it all back to the enactivist tenets.

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A Study of Preference and Comfort for Users Immersed in a Telepresence Robot

In this paper, we show that unwinding the rotations of a user immersed in a telepresence robot is preferred and may increase the feeling of presence or "being there". By immersive telepresence, we mean a scenario where a user wearing a head-mounted display embodies a mobile robot equipped with a 360° camera in another location, such that the user can move the robot and communicate with people around it. By unwinding the rotations, the user never perceives rotational motion through the head-mounted display while staying stationary, avoiding sensory mismatch which causes a major part of VR sickness. We performed a user study (N=32) on a Dolly mobile robot platform, mimicking an earlier similar study done in simulation. Unlike the simulated study, in this study there is no significant difference in the VR sickness suffered by the participants, or the condition they find more comfortable (unwinding or automatic rotations). However, participants still prefer the unwinding condition, and they judge it to render a stronger feeling of presence, a major piece in natural communication. We show that participants aboard a real telepresence robot perceive distances similarly suitable as in simulation, presenting further evidence on the applicability of VR as a research platform for robotics and human-robot interaction.

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Augmenting Immersive Telepresence Experience with a Virtual Body

We propose augmenting immersive telepresence by adding a virtual body, representing the user's own arm motions, as realized through a head-mounted display and a 360-degree camera. Previous research has shown the effectiveness of having a virtual body in simulated environments; however, research on whether seeing one's own virtual arms increases presence or preference for the user in an immersive telepresence setup is limited. We conducted a study where a host introduced a research lab while participants wore a head-mounted display which allowed them to be telepresent at the host's physical location via a 360-degree camera, either with or without a virtual body. We first conducted a pilot study of 20 participants, followed by a pre-registered 62 participant confirmatory study. Whereas the pilot study showed greater presence and preference when the virtual body was present, the confirmatory study failed to replicate these results, with only behavioral measures suggesting an increase in presence. After analyzing the qualitative data and modeling interactions, we suspect that the quality and style of the virtual arms, and the contrast between animation and video, led to individual differences in reactions to the virtual body which subsequently moderated feelings of presence.

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Unwinding Rotations Improves User Comfort with Immersive Telepresence Robots

We propose unwinding the rotations experienced by the user of an immersive telepresence robot to improve comfort and reduce VR sickness of the user. By immersive telepresence we refer to a situation where a 360\textdegree~camera on top of a mobile robot is streaming video and audio into a head-mounted display worn by a remote user possibly far away. Thus, it enables the user to be present at the robot's location, look around by turning the head and communicate with people near the robot. By unwinding the rotations of the camera frame, the user's viewpoint is not changed when the robot rotates. The user can change her viewpoint only by physically rotating in her local setting; as visual rotation without the corresponding vestibular stimulation is a major source of VR sickness, physical rotation by the user is expected to reduce VR sickness. We implemented unwinding the rotations for a simulated robot traversing a virtual environment and ran a user study (N=34) comparing unwinding rotations to user's viewpoint turning when the robot turns. Our results show that the users found unwound rotations more preferable and comfortable and that it reduced their level of VR sickness. We also present further results about the users' path integration capabilities, viewing directions, and subjective observations of the robot's speed and distances to simulated people and objects.

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Comfort and Sickness while Virtually Aboard an Autonomous Telepresence Robot

In this paper, we analyze how different path aspects affect a user's experience, mainly VR sickness and overall comfort, while immersed in an autonomously moving telepresence robot through a virtual reality headset. In particular, we focus on how the robot turns and the distance it keeps from objects, with the goal of planning suitable trajectories for an autonomously moving immersive telepresence robot in mind; rotational acceleration is known for causing the majority of VR sickness, and distance to objects modulates the optical flow. We ran a within-subjects user study (n = 36, women = 18) in which the participants watched three panoramic videos recorded in a virtual museum while aboard an autonomously moving telepresence robot taking three different paths varying in aspects such as turns, speeds, or distances to walls and objects. We found a moderate correlation between the users' sickness as measured by the SSQ and comfort on a 6-point Likert scale across all paths. However, we detected no association between sickness and the choice of the most comfortable path, showing that sickness is not the only factor affecting the comfort of the user. The subjective experience of turn speed did not correlate with either the SSQ scores or comfort, even though people often mentioned turning speed as a source of discomfort in the open-ended questions. Through exploring the open-ended answers more carefully, a possible reason is that the length and lack of predictability also play a large role in making people observe turns as uncomfortable. A larger subjective distance from walls and objects increased comfort and decreased sickness both in quantitative and qualitative data. Finally, the SSQ subscales and total weighted scores showed differences by age group and by gender.

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Analysis of User Preferences for Robot Motions in Immersive Telepresence

This paper considers how the motions of a telepresence robot moving autonomously affect a person immersed in the robot through a head-mounted display. In particular, we explore the preference, comfort, and naturalness of elements of piecewise linear paths compared to the same elements on a smooth path. In a user study, thirty-six subjects watched panoramic videos of three different paths through a simulated museum in virtual reality and responded to questionnaires regarding each path. Preference for a particular path was influenced the most by comfort, forward speed, and characteristics of the turns. Preference was also strongly associated with the users' perceived naturalness, which was primarily determined by the ability to see salient objects, the distance to the walls and objects, as well as the turns. Participants favored the paths that had a one meter per second forward speed and rated the path with the least amount of turns as the most comfortable

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Defining Preferred and Natural Robot Motions in Immersive Telepresence from a First-Person Perspective

This paper presents some early work and future plans regarding how the autonomous motions of a telepresence robot affect a person embodied in the robot through a head-mounted display. We consider the preferences, comfort, and the perceived naturalness of aspects of piecewise linear paths compared to the same aspects on a smooth path. In a user study, thirty-six subjects (eighteen females) watched panoramic videos of three different paths through a simulated museum in virtual reality and responded to questionnaires regarding each path. We found that comfort had a strong effect on path preference, and that the subjective feeling of naturalness also had a strong effect on path preference, even though people consider different things as natural. We describe a categorization of the responses regarding the naturalness of the robot's motion and provide a recommendation on how this can be applied more broadly. Although immersive robotic telepresence is increasingly being used for remote education, clinical care, and to assist people with disabilities or mobility complications, the full potential of this technology is limited by issues related to user experience. Our work addresses these shortcomings and will enable the future personalization of telepresence experiences for the improvement of overall remote communication and the enhancement of the feeling of presence in a remote location.

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The Plausibility Paradox for Resized Users in Virtual Environments

This paper identifies and confirms a perceptual phenomenon: when users interact with simulated objects in a virtual environment where the users' scale deviates greatly from normal, there is a mismatch between the object physics they consider realistic and the object physics that would be correct at that scale. We report the findings of two studies investigating the relationship between perceived realism and a physically accurate approximation of reality in a virtual reality experience in which the user has been scaled by a factor of ten. Study 1 investigated perception of physics when scaled-down by a factor of ten, whereas Study 2 focused on enlargement by a similar amount. Studies were carried out as within-subjects experiments in which a total of 84 subjects performed simple interaction tasks with objects under two different physics simulation conditions. In the true physics condition, the objects, when dropped and thrown, behaved accurately according to the physics that would be correct at that either reduced or enlarged scale in the real world. In the movie physics condition, the objects behaved in a similar manner as they would if no scaling of the user had occurred. We found that a significant majority of the users considered the movie physics condition to be the more realistic one. However, at enlarged scale, many users considered true physics to match their expectations even if they ultimately believed movie physics to be the realistic condition. We argue that our findings have implications for many virtual reality and telepresence applications involving operation with simulated or physical objects in abnormal and especially small scales.

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Human Perception-Optimized Planning for Comfortable VR-Based Telepresence

This paper introduces an emerging motion planning problem by considering a human that is immersed into the viewing perspective of a remote robot. The challenge is to make the experience both effective (such as delivering a sense of presence) and comfortable (such as avoiding adverse sickness symptoms, including nausea). We refer to this challenging new area as human perception-optimized planning and propose a general multiobjective optimization framework that can be instantiated in many envisioned scenarios. We then consider a specific VR telepresence task as a case of human perception-optimized planning, in which we simulate a robot that sends 360 video to a remote user to be viewed through a head-mounted display. In this particular task, we plan trajectories that minimize VR sickness (and thereby maximize comfort). An A* type method is used to create a Pareto-optimal collection of piecewise linear trajectories while taking into account criteria that improve comfort. We conducted a study with human subjects touring a virtual museum, in which paths computed by our algorithm are compared against a reference RRT-based trajectory. Generally, users suffered less from VR sickness and preferred the paths created by the presented algorithm.

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Virtual Reality for Robots

This paper applies the principles of Virtual Reality (VR) to robots, rather than living organisms. A simulator, of either physical states or information states, renders outputs to custom displays that fool the robot's sensors. This enables a robot to experience a combination of real and virtual sensor inputs, combining the efficiency of simulation and the benefits of real world sensor inputs. Thus, the robot can be taken through targeted experiences that are more realistic than pure simulation, yet more feasible and controllable than pure real-world experiences. We define two distinctive methods for applying VR to robots, namely black box and white box; based on these methods we identify potential applications, such as testing and verification procedures that are better than simulation, the study of spoofing attacks and anti-spoofing techniques, and sample generation for machine learning. A general mathematical framework is presented, along with a simple experiment, detailed examples, and discussion of the implications.

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