Social robots; topological semimetals; work-in-progress.
Social robot seeks to understand pedestrian behavior
In order for robots to circulate on sidewalks and mingle with humans in other crowded places, they’ll have to understand the unwritten rules of pedestrian behavior. As such, Stanford University researchers have created a short, non-humanoid prototype of just such a moving, self-navigating machine.
The robot is nicknamed “Jackrabbot” – after the jackrabbits often seen darting across the Stanford campus – and looks like a ball on wheels. It is equipped with sensors to be able to understand its surroundings and navigate streets and hallways according to normal human etiquette, the researchers explained who believe it is the prototype for a new generation of ‘social robot’ designed to learn how to move among humans.
The idea behind the work is that by observing how Jackrabbot navigates itself among students around the halls and sidewalks of Stanford’s School of Engineering, and over time learns unwritten conventions of these social behaviors, the researchers will gain critical insight in how to design the next generation of everyday robots such that they operate smoothly alongside humans in crowded open spaces like shopping malls or train stations. And by learning social conventions, the robot can be part of ecosystems where humans and robots coexist.
As robotic devices become more common in human environments, it becomes increasingly important that they understand and respect human social norms – and these human social conventions aren’t necessarily explicit nor are they written down complete with lane markings and traffic lights, like the traffic rules that govern the behavior of autonomous cars.
The researchers are using machine learning techniques to create algorithms that will allow the robot to recognize and react appropriately to unwritten rules of pedestrian traffic. The team’s computer scientists have been collecting images and video of people moving around the Stanford campus and transforming those images into coordinates. From those coordinates, they can train an algorithm.
For now, Jackrabbot already moves automatically and can navigate without human assistance indoors. The team is now fine-tuning the robot’s self-navigation capabilities outdoors with the next step the implementation of “social aspects” of pedestrian navigation such as deciding rights of way on the sidewalk based on an algorithm the team created that is able to automatically move the robot with social awareness.
Predicting previously unseen phenomena in exotic materials
Discovered just five years ago, topological semimetals are materials with unusual physical properties that could make them useful for future electronics and MIT researchers have reported a new theoretical characterization of topological semimetals’ electrical properties that accurately describes all known topological semimetals and predicts several new ones.
Guided by their model, the researchers also describe the chemical formula and crystal structure of a new topological semimetal that, they reason, should exhibit electrical characteristics never seen before.
The team explained that the properties of a material are generally sensitive to many external perturbations, but what’s special about these topological materials is they have some very robust properties that are insensitive to these perturbations, which is attractive because it makes theory very powerful in predicting materials, which is rare in condensed-matter physics.
Semimetals are somewhat like semiconductors. The researchers reminded that electrons in a semiconductor can be in either the valence band, in which they’re attached to particular atoms, or the conduction band, in which they’re free to flow through the material as an electrical current. Switching between conductive and nonconductive states is what enables semiconductors to instantiate the logic of binary computation.
Bumping an electron from the valence band into the conduction band requires energy, and the energy differential between the two bands is known as the band gap. In a semimetal — such as the much-studied carbon sheets known as graphene — the band gap is zero. In principle, that means that semimetal transistors could switch faster, at lower powers, than semiconductor transistors do, they said.
Now, researchers have shown that the momentum-energy relationships of electrons in the surface of a topological semimetal can be described using mathematical constructs called Riemann surfaces, and what makes a Riemann surface special is that it’s like a parking-garage graph: In a parking garage, if you go around in a circle, you end up one floor up or one floor down. This is exactly what happens for the surface states of topological semimetals. If you move around in momentum space, you find that the energy increases, so there’s this winding.
The researchers showed that a certain class of Riemann surfaces accurately described the momentum-energy relationship in known topological semimetals. But the class also included surfaces that corresponded to electrical characteristics not previously seen in nature.
Topographical semimetals have such tantalizing electrical properties that they’re worth understanding better, the researchers added.
If you are attending the Design Automation Conference this week, it’s always interesting to attend a DAC Work-in-Progress poster session that gives authors an opportunity to network with peer feedback on current work and preliminary results.