Tot i els problemetes tècnics del sensor d’infraroig. Ves per on, una foto-cèl·lula i un tubet de cartolina, muntats en un servo, són més eficaços (i barats!)
Archive for the ‘competicions’ Category
The Stanford Racing Team may have placed second at the DARPA Urban Challenge back in 2007, but they haven’t stopped pushing the limits of autonomous cars. At ICRA last week, Zico Kolter and his collaborators showed video of one of the most extreme stunts a robotic car has ever pulled off.
They taught the car to accelerate in reverse up to 25 miles per hour, then suddenly hit the brakes, turn the wheel, and start a 180-degree skid–ending up right in a desired parking spot. It’s not just a cool stunt–this research should give autonomous cars greater flexibility to deal with unexpected situations.
Reliably executing such a stunt isn’t easy. “Junior” (as the car is known) usually operates under closed-loop control, where real-time sensor data is used to continually adjust the controls. This works well for driving the car in a straight line, where the physics of the car’s motion are pretty straightforward to model. Unfortunately, the dynamics model tends to break down as the car enters the complex sliding turn. In the first clip of the video below, you can see Junior miss the mark under this type of control.
As an alternate approach, the team “taught” Junior the stunt through a basic demonstration. The researchers found that even though the sliding is complex to model, it’s a highly deterministic motion–by just blindly repeating the control inputs from the demonstration, the car usually ended up in the same place. But as you can see in the second attempt in the video, this open-loop control method also has a weakness: errors in the straight approach go uncorrected and cause big differences in Junior’s final position.
So to get the best result, the team combined approaches: keeping the car under closed-loop control during the well-modeled approach section, and then letting it transition to open-loop control for the final slide.
Most impressively, the Stanford team allowed the car to determine for itself which approach was better and when to smoothly switch between the two. The result (the third attempt in the video) lands the car right on target. For testing purposes the team decided to use cones rather than actual cars. Just in case.
Vía IEEE Spectrum
El proper dimecres 26 de maig, a les 12:00, al hall de l’ESTCE se celebrarà la competició de robots per a extinció d’incendis.
En esta competició, els estudiants de l’assignatura d’Intel·ligència Artificial, d’Enginyeria Informàtica, programaran el seu robot per a trobar i apagar un incendi en el menor temps possible.