# Solving the kidnapped robot problem using particle filters

 5 Hi, I was wondering if it would be possible to solve the kidnapped robot problem (localization after a random replacement) using our particle filter implementation. Well, it's much easier than I initially expected. Actually, it took only 4 lines of additional code to solve the problem :) Here's what I did: Each turn there's a 10% chance that the robot is replaced. Using the 'normal' solution for homework assignment 3.6 the algorithm is then (in most cases) unable to localize the robot again: Incorrect position belief after replacement So, in order to solve the problem all I had to do was to randomly seed some particles in the world for each iteration, which will result in something like this: Correct position belief thanks to randomly distributed particles And that's it! After a replacement the algorithm will converge to the correct position after 1-3 iterations. Of course, this is not a new idea by any means, but I was still surprised how easy it was to implement this. Maybe some of you will find it interesting as well :) I'll upload my code tomorrow, in the meantime you can see the algorithm working here: Youtube video I made some changes to the visualization, so that for each iteration the robot movement and the motion prediction is visualized as well. Have fun :) edit: Here's the code: Github Add random particles: for i in range(int(0.9 * N)): (Resampling wheel) for i in range(N - (int(0.9 * N))): r = robot() r.set_noise(bearing_noise, steering_noise, distance_noise) p3.append(r)  asked 12 Mar '12, 19:46 neb-2 86●2●5●7 accept rate: 0%

 0 Really interesting! I always had the intuition that it would be a good idea to add those random particles in each iteration, and this proves it useful. answered 13 Mar '12, 21:06 Manuel Araoz 1.4k●7●14●24 Yes, I think it's a good idea in general. Even when it's impossible that the robot is randomly replaced (e.g. if it's a car ;) there's still a slight chance that the particles won't converge to the correct position immediately. (14 Mar '12, 05:28) neb-2
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