Single drop cytometry onboard the International Space Station.

Real-time lab analysis is needed to support clinical decision making and research on human missions to the Moon and Mars. Powerful laboratory instruments, such as flow cytometers, are generally too cumbersome for spaceflight. Here, we show that scant test samples can be measured in microgravity, by a trained astronaut, using a miniature cytometry-based analyzer, the rHEALTH ONE, modified specifically for spaceflight. The base device addresses critical spaceflight requirements including minimal resource utilization and alignment-free optics for surviving rocket launch. To fully enable reduced gravity operation onboard the space station, we incorporated bubble-free fluidics, electromagnetic shielding, and gravity-independent sample introduction. We show microvolume flow cytometry from 10 µL sample drops, with data from five simultaneous channels using 10 µs bin intervals during each sample run, yielding an average of 72 million raw data points in approximately 2 min. We demonstrate the device measures each test sample repeatably, including correct identification of a sample that degraded in transit to the International Space Station. This approach can be utilized to further our understanding of spaceflight biology and provide immediate, actionable diagnostic information for management of astronaut health without the need for Earth-dependent analysis.

Hey Robot, Tell It to Me Straight: How Different Service Strategies Affect Human and Robot Service Outcomes.

With robots already entering simple service tasks in shops, it is important to understand how robots should perform customer service to increase customer satisfaction. We investigate two methods of customer service we theorize are better suited for robots than human shopkeepers: straight communication and data-driven communication. Along with an additional, more traditional customer service style, we compare these methods of customer service performed by a robot, to a human performing the same service styles in 3 online studies with over 1300 people. We find that while traditional customer service styles are best suited for human shopkeepers, robot shopkeepers using straight or data driven customer service styles increase customer satisfaction, make customers feel more informed, and feel more natural than when a human uses them. Our work highlights the need for investigating robot-specific best practices for customer service, but also for social interaction at large, as simply duplicating typical human-human interaction may not produce the best results for a robot.

It's not what you think: shaping beliefs about a robot to influence a teleoperator's expectations and behavior.

In this paper we present a novel design approach for shaping a teleoperator's expectations and behaviors when teleoperating a robot. Just as how people may drive a car differently based on their expectations of it (e.g., the brakes may be poor), we assert that teleoperators may likewise operate a robot differently based on expectations of robot capability and robustness. We present 3 novel interaction designs that proactively shape teleoperator perceptions, and the results from formal studies that demonstrate that these techniques do indeed shape operator perceptions, and in some cases, measures of driving behavior such as changes in collisions. Our methods shape operator perceptions of a robot's speed, weight, or overall safety, designed to encourage them to drive more safely. This approach shows promise as an avenue for improving teleoperator effectiveness without requiring changes to a robot, novel sensors, algorithms, or other functionality.

Still Not Solved: A Call for Renewed Focus on User-Centered Teleoperation Interfaces.

Teleoperation is one of the oldest applications of human-robot interaction, yet decades later, robots are still difficult to control in a variety of situations, especially when used by non-expert robot operators. That difficulty has relegated teleoperation to mostly expert-level use cases, though everyday jobs and lives could benefit from teleoperated robots by enabling people to get tasks done remotely. Research has made great progress by improving the capabilities of robots, and exploring a variety of interfaces to improve operator performance, but many non-expert applications of teleoperation are limited by the operator's ability to understand and control the robot effectively. We discuss the state of the art of user-centered research for teleoperation interfaces along with challenges teleoperation researchers face and discuss how an increased focus on human-centered teleoperation research can help push teleoperation into more everyday situations.