The gaze of a person tends to reflect their interest. This work explores what happens when this statement is taken literally and applied to robots. Here we present a robot system that employs a moving robot head with a screen-based eye model that can direct the robot's gaze to points in physical space and present a reflection-like mirror image of the attended region on top of each eye. We conducted a user study with 33 participants, who were asked to instruct the robot to perform pick-and-place tasks, monitor the robot's task execution, and interrupt it in case of erroneous actions. Despite a deliberate lack of instructions about the role of the eyes and a very brief system exposure, participants felt more aware about the robot's information processing, detected erroneous actions earlier, and rated the user experience higher when eye-based mirroring was enabled compared to non-reflective eyes. These results suggest a beneficial and intuitive utilization of the introduced method in cooperative human-robot interaction.

Lee Pace Has Big Hopes for's Fourth Season WIRED spoke to Lee Pace on the eve of the season finale of about clone consciousness, robot gods, and what's next for the newly renewed show. In the world of prestige sci-fi, reigns as the biggest sleeper hit. Mention the Apple TV+ adaptation of Isaac Asimov's classic series in a group of friends and you'll suddenly find everyone has been secretly watching it. Something of a flawed masterpiece, the show, which wraps its third season Friday, has been averaging about 1.5 million hours watched per week in the US over the last month, according to Luminate. Reasons for the show's popularity are many, but it's seemed to have gained traction as it's become more, well, relevant. The series, like Asimov's books, focuses on a group of economists using a predictive algorithm to guide the destiny of humanity through the collapse of a galactic empire.

The ability to display rich facial expressions is crucial for human-like robotic heads. While manually defining such expressions is intricate, there already exist approaches to automatically learn them. In this work one such approach is applied to evaluate and control a robot head different from the one in the original study. To improve the mapping of facial expressions from human actors onto a robot head, it is proposed to use 3D landmarks and their pairwise distances as input to the learning algorithm instead of the previously used facial action units. Participants of an online survey preferred mappings from our proposed approach in most cases, though there are still further improvements required.

Emotions, which are an important component of social interaction, can be studied with the help of android robots and their appearance, which is as similar to humans as possible. The production and customization of android robots is expensive and time-consuming, so it may be practical to use a digital replica. In order to investigate whether there are any perceptual differences in terms of emotions based on the difference in appearance, a robot head was digitally replicated. In an experiment, the basic emotions evaluated in a preliminary study were compared in three conditions and then statistically analyzed. It was found that apart from fear, all emotions were recognized on the real robot head. The digital head with "ideal" emotions performed better than the real head apart from the anger representation, which offers optimization potential for the real head. Contrary to expectations, significant differences between the real and the replicated head with the same emotions could only be found in the representation of surprise.

For the application described here external speakers and microphones are being used. The following actuators are The advancements in research on android robots open up available: more and more application opportunities. For example, android ERICA [1] was already tested for attentive listening, 1) upper eyelid down job interview practicing, speed date practicing and as a lab 2) eyeball left right guide. ERICA was proposed to be employed in other social 3) eyeball up down interaction tasks, e.g., as an attendant or a receptionist. Recent 4) lower eyelid up research suggests that android robots might be useful as 5) eyebrow up interaction partners for community-dwelling older adults with 6) eyebrow shrink little company [2]. Additionally android robots might be useful 7) mouth corner up tools in other research areas, too, e.g., in psychological studies 8) mouth corner back regarding emotional interactions [3].

There has been an exponential increase in R&D related to virtual reality, photorealistic computer animations and augmented reality. Researchers from around the globe are working in these domains and have been creating machines which have the abilities of a human -- or humanoid robots. This is an emerging research domain which is now playing a crucial role in robotics research. However, according to the uncanny valley theory, the humanoid objects which imperfectly resemble actual human beings provoke uncanny or strangely familiar feelings of revulsion in observers. The IEEE spectrum ranks robots into three categories, -- top-rated, creepiest and most wanted.

According to a recent TNG survey, 73 percent of job seekers in Sweden believe they've been discriminated against during the job application process. By replacing the human recruiter with Tengai, TNG and Furhat believe they can make the screening process more fair while still providing a "human" touch. "I was quite sceptical at first before meeting Tengai, but after the meeting I was absolutely struck," healthcare recruiter Petra Elisson, who has been involved in the testing, told the BBC. "At first I really, really felt it was a robot, but when going more deeply into the interview I totally forgot that she's not human." As for ensuring that Tengai doesn't reflect the biases of its creators and training data -- a problem that has cropped up with other AIs -- Furhat's chief scientist, Gabriel Skantze, told the BBC the company is making it a point to conduct test interviews with a diverse mix of recruiters and volunteers before Tengai is ever in the position to actually decide an applicant's employment fate.

The increased demand is adding to a big problem in the agricultural industry: a labor shortage that is unlikely to improve soon, according to farmers and researchers. It means berries that would otherwise be sold might instead rot in the field. Technologists think automation eventually could help producers pick specialty crops like berries, apples, peaches and snacking tomatoes, just as high-tech combines from companies such as Deere & Co. already are helping farmers of commodity crops harvest grains. Autonomous robots that run along tracks also are ferrying bins inside greenhouses, cutting down the walking workers have to do, growers and industry researchers say. But unlike in manufacturing, where artificial intelligence and computer vision power factory arms that move car parts or handle food in predetermined ways, agricultural fields pose a challenge for machines.

Google's best guess for the image?

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Boston Dynamics CEO Marc Raibert returns to TechCrunch Sessions Robotics and doesn't disappoint, talking about the Google acquisition, Masayoshi Son's 300-year technology investment plan, and SpotMini's "butt-cam." Playground founder and CEO Andy Rubin was also a guest at TC Sessions Robotics.