The folks at the SARTRE road train project have issued an update one year into their 3 year project. This is an EU-initiated project to build convoy technology, where a professional lead driver in a truck or bus is followed by a convoy of closely packed cars which automatically follow based on radio communications (and other signals) with the lead. They have released a new video on their progress from Volvo.

Two bits of robocar news from last week. I had been following the progress of the Stanford/VW team that was building a robotic Audi TT to race to the top of Pikes Peak. They accomplished their run in September, but only now made the public announcement of it. You can find photos and videos with the press release or watch a video on youtube.

Today, I was challenged with the question of how well robocars would deal with deer crossing the road. There are 1.5 million collisions with deer in the USA every year, resulting in 200 deaths of people and of course many more deer. Many of the human injuries and crashes have come from trying to swerve to avoid the deer, and skidding instead during the panic.

At present there is no general purpose computer vision system that can just arbitrarily identify things -- which is to say you can't show it a camera view of anything and ask, "what is that?" CV is much better at looking for specific things, and a CV system that can determine if something is a deer is probably something we're close to being able to make. However, I made a list of a number of the techniques that robots might have to do a better job of avoiding collisions with animals, and started investigating thoughts on one more, the "flying bumper" which I will detail below.

Spotting and avoiding the deer

• There are great techniques for spotting animal eyes using infrared light bouncing off the retinas. If you've seen a cheap flash photo with the "red eye" effect you know about this. An IR camera with a flash of IR light turns out to be great at spotting eyes and figuring out if they are looking at you, especially in darkness.
• A large number of deer collisions do take place at dusk or at night, both because deer move at these times and humans see badly during them. LIDAR works superbly in darkness, and can see 100m or more. On dry pavement, a car can come to a full stop from 80mph in 100m, if it reacts instantly. The robocar won't identify a deer on the road instantly but it will do so quickly, and can thus brake to be quite slow by the time it travels 100m.
• Google's full-map technique means the robocar will already have a complete LIDAR map of the road and terrain -- every fencepost, every bush, every tree -- and of course, the road. If there's something big in the LIDAR scan at the side of the road that was not there before, the robocar will know it. If it's moving and more detailed analysis with a zoom camera is done, the mystery object at the side of the road can be identified quickly. (Radar will also be able to tell if it's a parked or disabled vehicle.)
• They are expensive today, but in time deep infrared cameras which show temperature will become cheap and appear in robocars. Useful for spotting pedestrians and tailpipes, they will also do a superb job on animals, even animals hiding behind bushes, particularly in the dark and cool times of deer mating season.
• Having spotted the deer, the robocar will never panic, the way humans often do.
• The robocar will know its physics well, and unlike the human, can probably plot a safe course around the deer that has no risk of skidding. If the ground is slick with leaves or rain, it will already have been going more slowly. The robocar can have a perfect understanding of the timings involved with swerving into the oncoming traffic lane if it is clear. The car can calculate the right speed (possibly even speeding up) where there will be room to safely swerve.
• If the oncoming traffic lane is not clear, but the oncoming car is also a robocar, it might some day in the far future talk to that car both to warn it and to make sure both cars have safe room to swerve into the oncoming lane.
• Areas with major deer problems put up laser sensors along the sides of the road, which detect if an animal crosses the beam and flash lights. A robocar could get data from such sensors to get more advanced warning of animal risks areas.

Getting the deer to move

There might be some options to get the deer to get out of the way. Deer sometimes freeze; a "deer in the headlights." A robocar, however, does not need to have visible headlights! It may have them on for the comfort of the passengers who want to see where they are going and would find it spooky driving in the dark guided by invisible laser light, but those comfort lights can be turned off or dimmed during the deer encounter, something a human driver can't do. This might help the deer to move.

Many people wonder whether robocars will just suffer the curse of regular cars, namely traffic congestion. They are concerned that while robocars might solve many problems of the automobile, in many cities there just isn't room for more roads. Can robocars address the problems of congestion and capacity? What about combined with ITS (Intelligent Transportation Systems) efforts to make roads smarter for human driven cars?

I think the answer is quite positive, for a number of different reasons. I have added a new Robocar essay:

I've written before about solutions to "range anxiety" -- the barrier to adoption of electric cars which derives from fear that the car will not have enough range and, once out of power, might take a very long time to recharge. It's hard to compete with gasoline's 3 minute fill-up and 300 mile ranges. Earlier I proposed an ability to quickly switch to a rental gasoline car if running out of range.

I'm at the Pod Car City conference, taking place today and tomorrow in San Jose for PRT developers and customers. Some news tidbits from the conference:

There's news about the world's two small PRT (Personal Rapid Transit) projects, which are both fairly robocar like, in that they involve self-steered rubber tired vehicles.

The AutoNOMOS team at Freie Universität Berlin led by Raul Rojas has shown a demo of their robocar acting as what I have called a whistlecar. Their latest car, named "Made in Germany" performed an autonomous taxi pickup for the press which you can see played out in this video.

This weekend's announcement that Google had logged 140,000 miles of driving in traffic with their prototype robocars got lots of press, but it's not the only news of teams making progress. A team at TU Braunschweig in Germany has their own model which has been driving on ordinary city streets with human oversight. You can watch a video of the car in action though there is a lot of B-roll in that video, so seek ahead to 1:50 and particularly 3:20 for the inside view of the supervisor's hands hovering just over the self-turning steering wheel. There is some information on Stadtpilot here, but we can see many similarities, including the use of the Velodyne 64 line LIDAR on the roof and a typical array of sensors, and more use of detailed maps.

The team at Vislab in Milan has completed most of their Milan to Shanghai autonomous car journey which I have been following. You can read their blog or watch video (sometimes live) of their trip. A lot of the blog has ended up being not about the autonomous challenges, but just the challenges of taking a fleet of very strange looking vehicles in a convoy across Eastern Europe and Asia. For example, they have trucks which can carry their robocars inside, and once decided it was simpler to cross a border into Hungary this way. However, they left driving the vehicles, and the exit officials got very concerned that there was no record of the robocars coming into the country. I presume it wasn't hard to convince them they were not smuggling Hungarian robocars out.

Just released in a New York Times article and sidebar about highways and video, Google has unveiled an internal robot car project that has attained a remarkable level of robotic driving sooner than I and many others had predicted.

There was a bit of a stir when Google last week announced that one of the winners of their 10^100 contest would be Shweeb, a pedal-powered monorail from New Zealand that has elements of PRT. Google will invest $1M in Shweeb to help them build a small system, and if it makes any money on the investment, that will go into transportation related charities.

While I had a preference that Google fund a virtual world for developing and racing robocars I have come to love a number of elements about Shweeb, though it's not robocars and the PRT community seems to not think it's PRT. I think it is PRT, in that it's personal, public and, according to the company, relatively rapid through the use of offline stations and non-stop point to point trips. PRT is an idea from the sixties that makes sense but has tried for almost 50 years to get transit planners to believe in it and build it. A micro-PRT has opened as a Heathrow parking shuttle, but in general transit administrators simply aren't early adopters. They don't innovate.

What impresses me about Shweeb is its tremendous simplicity. While it's unlikely to replace our cars or transit systems, it is simple enough that it can actually be built. Once built, it can serve as a testbed for many of PRT's concepts, and go through incremental improvements.

An Italian team has built a prototype robot they call Dustbot which is aimed (in a backwards way) at the deliverbot vision.

Here's an idea that seems a bit wild and scary at first, but it's doable today and has broad benefits: Small aircraft that don't have landing gear, but instead land and take off from robotic "can't miss" platforms pulled by cables on short airfields.

UPDATE: Some updated ideas and a link to a funded research project looking at similar ideas.

For every small aircraft purchaser, a big decision is whether to get retractable landing gear. They are very expensive, and create a risk of failure, but your plane will fly a lot faster and be more fuel efficient if you get them. What if we could leave the landing gear on the ground?

Imagine a wheeled platform on the runway with robotic control and a variety of systems to perfectly track an approaching aircraft. Pulled by cables, it can accelerate at several "g"s forward and back and left and right. As the aircraft approaches it tracks it and the cockpit display indicates positive lock. If the plane veers left, it veers left. If the plane speeds up it speeds up. Pretty much no matter what the pilot or winds do (other than missing the runway entirely) the plane can't miss landing on it. It's spring loaded so even if the landing is a bit hard the shock is cushioned. Done right, it's just like having fancy shock absorbing landing gear.

This story from the Register about a test at the Stanford VAIL Lab reports an interesting result. They created a fake robocar, with a human driver hidden in the back. The test subjects then were told they could push the autopilot button and use the car. And they did, immediately picking up their newspapers to read as they would in a taxi (which is what they really were in.)

Today marks the start of a remarkable robocar trek from Italy to China. The team from the Vislab International Autonomous Challenge start in Italy and will trek all the way to Shanghai in electric autonomous vehicles, crossing borders, handling rough terrain and going over roads for which there are no maps in areas where there is no high-accuracy GPS.

I don't often write about robots that don't go on roads, but last night I stopped by Willow Garage, the robot startup created by my old friend Scott Hassan. Scott is investing in building open robotics platforms, and giving much of it out free to the world, because he thinks progress in robotics has been far too slow.

Last week, I attended a talk by Marc Raibert the former MIT Professor who founded Boston Dynamics, the makers of the BigDog 4-legged walking robot. If you haven't seen the various videos of BigDog you should watch them immediately, as this is some of the most interesting work in robotics today.

Walking pack robots like BigDog have a number of obvious applications, but at present they are rather inefficient. BigDog is powered by a a 2 stroke compressor that drives hydraulics. That works well because the legs don't need engines but can exert a lot of force. However, its efficiency is in the range of 2 gallons per mile, though this is just a prototype level. It is more efficient on flat terrain and pavement, but of course wheels are vastly more efficient there. As efficient as animals are, wheeled vehicles are better if you don't make them heavy as tanks and SUVs.

BigDog walks autonomously but today is steered by a human, or in newer versions, can follow a human walking down a trail, walking where she walked. In the future they want to make an autonomous delivery robot that can be told to take supplies to troops in the field, or carry home a wounded soldier.

I wondered if BigDog isn't trying too hard to be a mule, carrying all the weight up high. This makes it harder for it to do its job. If it could just tow a sledge (perhaps a container with a round teflon bottom with some low profile or retractable wheels) it might be able to haul more weight. Particularly because it could pay out line while negotiating something particularly tricky and then once stable again, reel in the line. This would not work if you had to go through boulders that might catch the trailer but for many forms of terrain it would be fine. Indeed, Boston Dynamics wants to see if this can work. On the other hand, they did not accept my suggestion that they put red dye in the hydraulic fluid so that it spurts red blood if damaged or shot.

The hydraulic design of BigDog made me wonder about applications to robocars. In particular, it seems as though it will be possible to build a light robocar that has legs folded up under the chassis. When the robocar got to the edge of the road, it could put down the legs and be able to climb stairs, go over curbs, and even go down dirt paths and rough terrain. At least a lightweight single person robocar or deliverbot might do this.

At the positive end of my prediction that robocars will enable people to travel in "the right vehicle for the trip" and given that most trips are short urban ones, it follows that most robocars, if we are efficient, will be small light vehicles meant for 1-2 people, with a lesser number of larger ones for 4-5 people.

Last week, Volvo was demoing some new collision avoidance features in their S60. I've talked about the S60 before, as it surprised me putting pedestrian detection into a car before I expected it to happen. Unfortunately in an extreme case of demo disease known to all computer people, somebody has made an error with the battery, and in front of a crowd of press, the car smashed into the truck it was supposed to avoid. The wired article links to a video.

This weekend I attended the annual "Robogames" competition, which took place here in the Bay Area. Robogames is mostly a robot battle competition, with a focus on heavily armed radio-controlled robots fighting in a protected arena. For several years robot fighting was big enough to rate some cable TV shows dedicated to it. The fighting is a lot of fun, but almost entirely devoid of automation -- in fact efforts to use automation in battle robots have mostly been a failure.

The RC battles are fierce and violent, and today one of the weapons of choice is something heavy that spins at very high speed so that it builds up a lot of angular momentum and kinetic energy, to transfer into the enemy. People like to see robots flying through the air and losing parts to flying sparks. (I suspect this need to make robots very robust against attack makes putting sensors on the robots for automation difficult, as many weapons would quickly destroy a lot of popular sensors types.) The games also featured a limited amount of automated robot competition. This included some lightweight (3lb and 1lb) automated battles which I did not get to watch, and some some hobby robot competitions for maze-running, line following, ribbon climbing and LEGO mindstorms. There was also semi-autonomous robot battle called "kung fu" where humanoid robots who take high level commands (like punch, and step) try to push one another over. There is also sumo, a game where robots must push the other robot out of the ring.

I had hoped the highlight would be the Robo-magellan contest. This is a hobbyist robot car competition, usually done with small robots 1 to 2 feet in length. Because it is hobbyists, and often students, the budgets are very small, and the contest is very simple. Robots must make it through a simple outdoor course to touch an orange cone about 100 yards away. They want to do this in the shortest time, but for extra points they can touch bonus cones along the way. Contestants are given GPS coordinates for the target cones. They get three tries. In this particular contest, to make it even easier, contestants were allowed to walk the course and create some extra GPS waypoints for their robots.

These extra waypoints should have made it possible to do the job with just a GPS and camera, but the hobbyists in this competition were mostly novices, and no robot reached the final cone. The winner got within 40 feet on their last run, but no performance was even remotely impressive. This was unlike past years, where I was told that 6 or more robots would reach the target and there would be real competition. This year's poor showing was blamed on budgets, and the fact that old teams who had done well had moved on from the sport. Only 5 teams showed up.

The robots were poor for sensors. While all would have a GPS, in 1 or 2 cases the GPS systems failed and the robots quickly wandered into things. A few had sonar or touch-bars for obstacle detection, but others did not, and none of them did their obstacle detection well at all. For most, if they ran into something, that was it for that race. Some used a compass or accelerometers to help judge when to turn and where to aim, since a GPS is not very good as a compass.