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Is speed map a good idea

asked 2018-10-29 17:10:02 -0500

AutoCar gravatar image

Hi, I am developing an algorithm for my robot to race in a fixed track, something like this picture ( ). The robot uses particle filter to locate itself. But I am not sure what the best "planning" method is for this kind of fixed track. I do not want to use ROS planner but instead am thinking a "Speed map" approach. The idea is to generate a 2D grid map. Each grid has a speed and direction value. Once the robot find where it is, it can grab the speed from this map. Is this a good method? Is there existing software for this?

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answered 2018-10-30 04:08:31 -0500

updated 2018-10-30 04:17:28 -0500

Your idea reminds me a bit of artificial potential fields (they've been used for robot control for a long time). It sounds like your idea could work really well for your problem. One thing to keep in mind though: You are assuming that the control output (speed + direction) only depends on the robot's current position (which grid cell it's in). In reality, the control output probably depends on more inputs: the robot's position, orientation, steering angle and velocity.

I'm not aware of existing implementations of that idea, but there may very well be some.

Oh, one more thing: your grid map isn't really a planning method; it's Memoization. You will still need a planning (or learning) method to fill in the grid map. Perhaps SBPL can be used for that; the library's authors have used it for the DARPA urban challenge before (see SBPL publications). But perhaps you'll want to try something simpler first.

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Thanks. I just want to make sure I am not totally out of line or reinvent the wheel.

As for the planning part, since the track is fixed, I can set the desired speed before hand. And why the robot is in the grid, I just set it to that speed.

AutoCar gravatar image AutoCar  ( 2018-10-30 15:05:58 -0500 )edit

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Asked: 2018-10-29 17:10:02 -0500

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Last updated: Oct 30 '18