Not Moonbounce, Rather Building- And Pedestrian-Bounce
/In late January, an Alphabet-owned Waymo self-driving car was cruising near an elementary school in Santa Monica, California, when a young child suddenly darted into the street. Waymo’s LiDAR sensors detected the student, who had just emerged from behind a parked SUV, but it was too late. Despite slamming on the brakes and slowing from 17 to six mph, the driverless car struck the child, knocking them to the pavement. Luckily, reports show that the child only suffered minor injuries, but that’s likely little comfort to parents whose children live in the growing number of cities where driverless cars operate.
In this case, the Waymo detected the child once they came into view—but what if it could have “seen” them from around the corner? That is the general idea behind new research emerging out of the University of Pennsylvania, where a team of engineers have developed a sensor system that uses radio waves to help robots detect objects (or people) hidden behind walls.
“Robots and autonomous vehicles need to see beyond what’s directly in front of them. This is an important step toward giving robots a more complete understanding of their surroundings.”
In testing, the HoloRadar system was mounted on small mobile robots and successfully identified people through walls while roaming around campus. Though the research is still in its early stages, the team is optimistic that its sensor system could be integrated into robots to help them navigate their surroundings more effectively. For self-driving cars, it just might make the difference in preventing a future collision.
Though there are some notable exceptions (Tesla chief among them), most emerging self-driving vehicles rely on a combination of cameras, radar, and LiDAR sensors to “see” the world around them. LiDAR systems emit millions of laser pulses in all directions and measure how quickly those pulses bounce back. The systems then use that data to almost instantaneously generate a highly detailed 3D map of the vehicle’s surroundings.
But LiDAR has limitations. Large buildings or other obstacles can block its laser pulses, preventing it from detecting what is hidden around a corner. To try and solve that problem, Zhao and his colleagues decided to explore an approach largely abandoned by autonomous vehicle (AV) companies: radio waves. Researchers had previously avoided radio signals because they produce much longer wavelengths than visible light, resulting in lower resolution and less clarity when detecting objects. Image clarity, in that case, is crucial to figuring out if that blob in the street is a floating plastic bag or a scurrying pet. The team from Penn eventually realised that this apparent limitation could actually be an advantage when it comes to LiDAR seeing around corners.
Radio waves emitted by a robot that strike a wall or other surface are much larger than the small surface variations on that wall. As a result, only part of the radio signal continues past the barrier, while a significant portion is reflected back toward its source. The researchers explain that this effect essentially causes surfaces to behave like mirrors, reflecting radio signals in predictable patterns.
