Predictive Policing and Wilderness Search and Rescue -- Can AI Help?

Santa Cruz police officers arresting a woman at a location
flagged by a computer program as high risk for car burglaries.
(Photo Credit: ERICA GOODE)

I came across an article recently talking about how Santa Cruz police department has been testing a new method where they use computer programs to predict when and where crimes are likely to happen and then send cops to that area for proactive policing. Although the movie "Minority Report" by Tom Cruise immediately came to my mind, that was actually not the same. The computer program was developed by a group of researchers consisting of two mathematicians, an anthropologist, and a criminologist. The program uses a mathematical model to read in crime data in the same area for the past 8 years and then predict time and location of areas with high probability for certain type of crimes. The program apparently can read in new data daily. This kind of program is attracting interests from law enforcement agencies because the agencies are getting a lot more calls for service when the number of staff is much less due to poor economy. This requires them to deploy resources more effectively. The article did not disclose much detail about the mathematical model (because it is a news article, not a research paper, duh), but it is probably safe to assume the model tries to identify patterns from past crime data and then assign probabilities to each grid cell (500 feet by 500 feet).

A multi-modal probability distribution predicting likely places
to find the missing person and a UAV path generated by algorithm.

I found this article especially interesting because in my research I am solving a similar problem with a similar approach. My research focuses on how an Unmanned Aerial Vehicle (UAV) can be used more efficiently and effectively by searchers and rescuers in wilderness search and rescue operations. One part of the problem is trying to predict where are likely places the lost person might be found. Another part of the problem is to generate an efficient path for the UAV so it will cover those high probability areas well with limited flight time. I've also developed a mathematical model (a Bayesian approach) that uses terrain features to predict the lost person's movement behavior, and also incorporate human behavior patterns from past data in the form of GPS track logs.

In both cases, the problems arise because of limited resources.

It is very important to remember that no one has the real crystal ball, so predictions can not be 100% correct. Also the prediction is in the form of a probability distribution, meaning in the long run (with many cases), the predictions are likely correct a good percentage of the time, but for each individual cases, the prediction could very possibly be wrong. This applies to both predictive policing and wilderness search and rescue.

Another important question to ask is how do you know your model is good and useful. This is difficult to answer because, again, we don't know the future. It is possible to pretend part of our past data is actually from "the future," but there are many metrics, what if the model performed well with respect to one metric, but performed terribly with respect to another metric? Which metric to use might be related to the individual case. For example, should number of arrests be used to measure the effectiveness of the system? Maybe by sending police officers to certain areas would scare off criminals and actually result in a reduction in number of arrests.

The predictive policing problem probably holds an advantage over the wilderness search and rescue problem because a lot more crimes are committed than people getting lost in the wilderness resulting in a much richer dataset. Also path planning for police offices is a multiagent problem while we only give the searchers and rescuers one UAV.

One problem with such predictive systems is that users might grow to fully rely on the system. This is an issue of Trust in Automation. Under-trust might waste resources, but over-trust might also lead to bad consequences. One thing to remember is that no matter how complicated the mathematical model is, it is still a simplified version of the reality. Therefore, calibrating the user's trust becomes an important issue and the user really need to know the strength of the AI system and also the weakness of the AI system. The product of the AI system should be complementary to the user to reduce the user's work and remind the user places that might be overlooked. The user also should be able to incorporate his/her domain knowledge/experience into the AI system to manage the autonomy. In my research, I am actually designing tools that allow users to take advantage of their expertise and manage autonomy at three different scales. I'll probably talk more about that in another blog post.

Anyway, it's good to see Artificial Intelligence used in yet another real life applications!







You shall not carry a brass knuckle in Texas because it is considered an illegal weapon (but in California you'll be just fine). Don't you love the complication of the US legal system, which by the way, serves big corporations really well.

Robot of the Day: Mars Pathfinder and the Sojourner Rover

On July 4th, 1997, which also happened to be the Independence Day of the United States, the Mars Pathfinder successfully landed on Mars. It made history because it was:

• The third lander (since the two Vikings) successfully landing on Mars.
• The first time a bouncing air bag landing mechanism was used for a lander.
• The first time a robot rover was successfully deployed.
• The first time a space mission was broadcasted on the Internet live.

After the successful landing, images of the mysterious red planet from the planet surface was broadcasted "live" on the Internet. This event had profound and extraordinary impacts on the public interests in space exploration, robotics technology, and web technologies, and inspired a generation of potential roboticists.

The Mars Pathfinder consisted of a lander and lightweight wheeled robotic rover named Sojourner (named after a a nineteenth-century black feminist and campaigner for the abolition of slavery). It was wrapped in large airbags. After entering the Martian atmosphere, a parachute was first deployed to slow down the falling of the capsule. Then a self-inflating airbag system in the shape of a tetrahedral was released, which "soft" landed on the terrain surface of Mars and rolled and bounced up and down all over the place. After the tetrahedral finally stopped rolling, the airbags were deflated and the lander unfolded itself, letting lose of the robotic rover. It is simply mind-boggling to see how the lander and the rover survived such vigorous movements, especially when one would have expected the scientific equipments on board to be very delicate devices. The video below shows some animations and footage of the landing process.

The main objective of the mission was to demonstrate it is possible to perform extraterrestrial exploration with low cost. As added benefit, the Mars Pathfinder also conducted some scientific experiments with a cameras, atmospheric structure instruments, and a spectrometer on the rover. The rover had six independently-controlled wheels and performed rock analysis as it roved about not far from the lander. The video below shows some footage of the rover moving about.

Roughly three months later, the mission control lost contact with the Pathfinder, but the mission had exceeded its goals just during the first month. Although still visible from Mars Reconnaissance Orbiter up high in the Martian sky, the robot (system) had become fully autonomous and just wondered about like a lonely ghost. Just like its name suggests, it had finally broken free from its human masters and became a free, uh, robot!

When I interned at NASA Ames in California in 2009, I was very fortunate to spot a prototype of the Sojourner Rover at the Intelligent Robotics Group (see pic on the left). I am strong believer in space colonization because we must "spread the seeds of human civilization" before we totally destroy our planet earth. And to make space colonization possible, we totally need robots that can build habitats for us. I wish the government would spend more on robotics and space exploration instead of sending troops to other countries to torture their citizens under the name of spreading "democracy" and "freedom".


Anyway, if you want to find out more about the Mars Pathfinder, you can watch "The Pathfinders" Documentary on YouTube.



Picture of the Day:

Photo of a meteor taken by astronaut from the International Space Station.

AI Robot Related Conferences and Journals For My Research (Part 1)

Since my dissertation will be a paper-based dissertation, I need to publish a bunch of papers. My advisor has asked me to think about a schedule and a plan for where to submit my papers. There are many AI robot related conferences and journals out there. However, only some of them are quality ones. In this blog post I'll list some of the top ones, discuss what each conference is about, and identify paper submission deadlines. So if you are also thinking about publishing papers in the AI robot field, look no further. I've already done the homework for you.

Top Conferences
==================================================================

AAAI -- Association for the Advancement of Artificial Intelligence

AAAI is a top-tier multi-track conference held yearly. It is a prestigious conference with an acceptance rate roughly between 25% and 30%. A very wide range of AI topics are covered at the conference including multi-agent systems, machine learning, computer vision, knowledge representation and reasoning, natural language processing, search and planning, integrated intelligence, robotics, and etc. The conference also includes many tutorials, workshops, consortium, exhibitions, and competitions.

The AAAI conference is devoted to advancing the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. It also aims to increase public understanding of artificial intelligence, improve the teaching and training of AI practitioners, and provide guidance for research planners and funders concerning the importance and potential of current AI developments and future directions.

I have been fortunate enough to attend the AAAI conference twice (2007 in Vancouver, BC and 2010 in Atlanta, GA, USA) and published a paper at the 2010 conference under the Integrated Intelligence track. I was also invited to present a poster for the same paper. In that same conference, I watched and blogged about the Robot Chess Competition.

The next AAAI conference AAAI-12 (the 26th) will be held at Toronto, Ontario, Canada.
Conference Dates: July 22-26, 2012
Submission Deadline: February 8, 2012 (roughly)


IJCAI -- International Joint Conference on Artificial Intelligence

IJCAI is also a top-tier multi-track conference held biennially in odd-numbered years. The acceptance rate for this conference is roughly between 20% and 26%, which makes the it even more selective than many AI journals. It also covers a wide range of AI topics such as multiagent systems, uncertainly in AI, and robotics and vision. One difference between AAAI and IJCAI is that IJCAI is more of a real international conference with paper submissions from all over the world.

One thing great about this conference is that all proceedings of the papers are free to all from their web sites. They also provide video recordings of each session at the conference, so you don't have to be present at the conference and can still watch all the presentations as if you were really there. This is very rare for AI robotics conferences as far as I know and it is a wonderful service they are providing!!

I have not had a chance to submit anything to IJCAI. If possible, I'd really like to give it a try for the next one, and if you read the next line, you'll know why.

The next IJCAI conference IJCAI-13 (the 23rd) will be held at Beijing, China.
Conference Dates: August 3-9, 2013
Submission Deadline: January 25, 2013 (roughly)

AI Robot Related Conferences and Journals For My Research Part 2


Picture of the Day:

We found this very friendly black poodle wandering on the street, so we took her home while we looked for her owner. She was such a wonderful little thing and our entire family loved her. Luckily the owner saw our posts online and contacted us. My daughter was very sad to see her go, but we are very happy that she could finally go home! So if you have a pet, make sure you have a tag with your address and phone number. Could be real handy at times!

Thrun and Novig Offer Free "Intro to AI" Course at Stanford

If you have studied Artificial Intelligence before, you probably already know who Thrun and Novig are. For those who have no idea, let me first introduce the two prominent researchers in the AI community.

Sebastian Thrun is a Computer Science professor at Stanford University. He also works for Google at the same time. His most famous achievement was to lead the team that won the 2005 DARPA Grand Challenge, a competition where unmanned cars had to cross the Nevada desert fully autonomously. He also helped develop the Google self-driving car, which has been secretly driving all over California freeways and local streets (I am not really sure if this is legal of not). He is also the co-author of a wonderful book, Probabilistic Robotics, which should be, in my opinion, a must read for robotics researchers. I have had the pleasure of meeting him briefly at a AAAI conference.

Peter Norvig, who had worked for Sun and NASA before, is now director of research at Google. He is the co-author of the most famous AI textbook, Artificial Intelligence: A Modern Approach, a book any AI researcher should have in his/her collection. This book was also my textbook when I took the Intro to AI course at BYU. I was fortunate enough to attend a presentation Dr. Norvig gave at Carnegie Melon Ames Campus and asked him many questions (maybe too many). His current research interest lies in data-driver approaches to solving AI problems, which should comes to no surprise since he works for Google.

So here's the great news!! The two will be teaching the course Introduction to Artificial Intelligence at Stanford during the Fall Semester of 2011 and have decided to open the course to everyone for free. This means not only all the course materials will be publicly available, including videos of the course in 15 minute chunks for your convenience (lecture runs 75 minutes long), you can also do all the homework/course assignments/quizzes and take exams just like a real Stanford student. They will be graded and if you pass the course, you get a certificate of completion from the instructors. You can also compare your grade to the grades of the real Stanford students.

Anyone can sign up for the course for free at this web page up to September 10th. Many of my friends have already signed up. The Intro to AI class I took at BYU is one of my favorite classes ever in my entire life. I am sure the one offered at Stanford will be just as fun. I, however, don't plan to do any of the assignments or take any of the exams, :) and will only enjoy the videos of the lectures.

I think it is wonderful that people are offering their teaching and knowledge to the entire world for free, because of their love and passion for the subjects. In the past, MIT has offered free courses online and there is, of course, the famous and wonderful Kahn Academy. If we all contribute a little to the world without thinking about what we get in return, we can make the world a better place every day!

Picture of the Day:

I was at the little restaurant called The Italian Place enjoying lunch when I found this on my computer. Is this because of the Italian connection?

Robot of the Day: Clocky, R2-D2-like Alarm Clock on Steroid

Clocky is a robot alarm clock created by Gauri Nanda, a graduate from the MIT Media Lab. Unlike other stationary alarm clocks, this R2-D2 or Droid-like little robot rolls off your nightstand when it's time to wake up, and rolls all over your room while making cute noises. This also means, in order to stop the alarm, you can't just keep hitting the snooze button and have to really get up to chase down Clocky in order to turn it off. What a great idea!! In fact, this idea is so great that after graduation, Nanda started her own company, Nanda Home, to commercialize the product and have already made millions.

This is yet another one of those innovative ideas of using simple robots to solve real world problems. Clocky is not a complicated robot at all. In fact, it doesn't really have any navigational capabilities or make any intelligent decisions. It just runs around randomly, looks cute, and annoys the hell out of you. But you have to admit, it does get the job done. The only possible downside is that you might be so mad after waking up and want to throw it out of the window. Although it's build to withstand falls from your tables or nightstands, but it probably won't survive free fall from anything higher than the second floor. The robot sells for around $49, and you can find many with different colors from places such as Amazon. I must admit, this little robot makes a great gift idea. So if you ever plan to send me a gift...cough...you know...

Last year, the company made Clocky a cousin and named it Tocky. Tocky rolls around like a ball, can also play MP3 files, and is $20 more expensive. So pick the one that's easier to catch for you.

I really wonder if someone will make another robot that will chase Clocky down and shuts it off, so we can go back to our sweet dreams uninterrupted. I can imagine how hard it is to develop such a robot, because you probably have to understand concepts such as Kalman Filter or Particle Filter.






If it has a wiki page, it's worth something! (Now someone creates a wiki page for me please! :)




Video of the Day:

Check out Flying Alarm Clock. At first I thought this is Clocky moving in 3D. But I was wrong!