Marynel Vázquez

3D Printing Pneumatic Device Controls with Variable Activation Force Capabilities

We explore 3D printing physical controls whose tactile response can be manipulated programmatically through pneumatic actuation. In particular, by manipulating the internal air pressure of various pneumatic elements, we can create mechanisms that require different levels of actuation force and can also change their shape. We introduce and discuss a series of example 3D printed pneumatic controls, which demonstrate the feasibility of our approach. This includes conventional controls, such as buttons, knobs and sliders, but also extends to domains such as toys and deformable interfaces. We describe the challenges that we faced and the methods that we used to overcome some of the limitations of current 3D printing technology. We conclude with example applications and thoughts on future avenues of research.

Helping visually impaired users properly aim a camera

We evaluate three interaction modes to assist visually impaired users during the camera aiming process: speech, tone, and silent feedback. Our main assumption is that users are able to spatially localize what they want to photograph, and roughly aim the camera in the appropriate direction. Thus, small camera motions are sufficient for obtaining a good composition. Results in the context of documenting accessibility barriers related to public transportation show that audio feedback is valuable. Visually impaired users were not affected by audio feedback in terms of social comfort. Furthermore, we observed trends in favor of speech over tone, including higher ratings for ease of use. This study reinforces earlier work that suggests users who are blind or low vision find assisted photography appealing and useful.

Spatial and other social engagement cues in a child-robot interaction: effects of a sidekick

In this study, we explored the impact of a co-located sidekick on child-robot interaction. We examined child behaviors while interacting with an expressive furniture robot and his robot lamp sidekick. The results showed that the presence of a sidekick did not alter child proximity, but did increase attention to spoken elements of the interaction. This suggests the addition of a co-located sidekick has potential to increase engagement but may not alter subtle physical interactions associated with personal space and group spatial arrangements. The findings also reinforce existing research by the community on proxemics and anthropomorphism.

A deceptive robot referee in a multiplayer gaming environment

We explore deception in the context of a multi-player robotic game. The robot does not participate as a competitor, but is in charge of declaring who wins or loses every round. The robot was designed to deceive game players by imperceptibly balancing how much they won, with the hope this behavior would make them play longer and with more interest. Inducing false belief about who wins the game was accomplished by leveraging paradigms about robot behavior and their better perceptual abilities. There were participants who found the balancing strategy favorable after being debriefed, and others who showed less interest mostly because of their perceived level of unfairness. Trust, suspicion, motivation, and appeal were evaluated by altering the robot behavior during gameplay. Post-briefing results include the finding that participants are more accepting of the use of lying by our robot as opposed to robots in general. Factors pertaining to gameplay, this robot, and deceptive robotics in general are also discussed.

An Assisted Photography Framework to Help Visually Impaired Users Properly Aim a Camera

We propose an assisted photography framework to help visually impaired users properly aim a camera and evaluate our implementation in the context of documenting public transportation accessibility. Our framework integrates user interaction during the image capturing process to help users take better pictures in real time. We use an image composition model to evaluate picture quality and suggest providing audiovisual feedback to improve users’ aiming position. With our particular framework implementation, blind participants were able to take pictures of similar quality to those taken by low vision participants without assistance. Likewise, our system helped low vision participants take pictures as good as those taken by fully sighted users. Our results also show a positive trend in favor of spoken directions to assist visually impaired users in comparison to tone and silent feedback. Positive usefulness ratings provided by full vision users further suggest that assisted photography has universal appeal.

Parallel detection of conversational groups of free-standing people and tracking of their lower-body orientation

Appropriate robot behavior in public, open spaces cannot occur without the ability to automatically detect conversational groups of free-standing people. To this end, we propose an alternating optimization procedure that estimates lower body orientations and detects groups of interacting people. The first task is achieved by tracking the direction of the lower body of the people in the scene based on their position, their head orientation, the location of objects of interest in their vicinity, and their groups. For the second task, we propose a new group detection algorithm based on F-formation detection. This method can reason about lower body orientation distributions, and generates soft group assignments for the orientation trackers. We evaluate the proposed approach on a publicly available dataset, and show that it can improve state-of-the-art detection of non-interacting people without sacrificing group detection accuracy. This is particularly useful for robots since it provides more opportunities for starting interactions and can help estimate disengagement.

An assisted photography method for street scenes

We present an interactive, computational approach for assisting users with visual impairments during photographic documentation of transit problems. Our technique can be described as a method to improve picture composition, while retaining visual information that is expected to be most relevant. Our system considers the position of the estimated region of interest (ROI) of a photo, and camera orientation. Saliency maps and Gestalt theory are used for guiding the user towards a more balanced picture. Our current implementation for mobile phones uses optic flow to update the internal knowledge of the position of the ROI and tilt sensor readings to correct non horizontal or vertical camera orientations. Using ground truth labels, we confirmed our method proposes valid strategies for improving image composition. Future work includes an optimized implementation and user studies.

Facilitating photographic documentation of accessibility in street scenes

We present two interactive approaches for assisting users with visual impairments during photographic documentation of transit accessibility. We are working on an application for camera-enabled mobile devices that drives image composition towards highlighting visual information that is expected to be most relevant. In one interaction modality the user is guided trough small device motions that are expected to center the estimated region of interest in street photographs. In the other modality, the user captures the scene while pictures are processed, and the system alerts when enough data has been collected. The image that best aligns with our attention-getting composition model is then selected for documentation purposes. The specific design of these interactions is evolving to promote small motion behaviors by the user. Future work includes user studies.

ShakeTime!: a deceptive robot referee

We explore deception in the context of a multi-player robotic game. The robot does not participate as a competitor, but is in charge of declaring who wins or loses every round. The robot was designed to deceive game players by imperceptibly balancing how much they won, with the hope this behavior would make them play longer and with more interest. Inducing false belief about who wins the game was accomplished by leveraging paradigms about robot behavior and their better perceptual abilities. Results include the finding that participants were more accepting of lying by our robot than for robots in general. Some participants found the balancing strategy favorable after being debriefed, while others showed less interest due to a perceived level of unfairness.

Maintaining awareness of the focus of attention of a conversation: A robot-centric reinforcement learning approach

We explore online reinforcement learning techniques to find good policies to control the orientation of a mobile robot during social group conversations. In this scenario, we assume that the correct behavior for the robot should convey attentiveness to the focus of attention of the conversation. Thus, the robot should turn towards the speaker. Our results from tests in a simulated environment show that a new state representation that we designed for this problem can be used to find good policies for the robot. These policies can generalize across interactions with different numbers of people and can handle various levels of sensing noise.