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Esse commit está contido em:
Laurent Eschenauer
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Copyright (c) 2012 Bernhard K. Weisshuhn (bkw@codingforce.com) and contributors
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.
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This code includes code from the following MIT licenced projects:
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* https://github.com/bjnortier/autopilot
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* https://github.com/Mikhus/canv-gauge
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# ardrone-autonomy
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Provides key building blocks to create autonomous flight applications
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with the AR.Drone. Works as a layer on top of the [node-ar-drone]() library.
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This work is based on the [Visual Navigation for Flying Robots](http://vision.in.tum.de/teaching/ss2013/visnav2013) course.
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**This work has just started, this branch is the development branch, there are no packaged release yet.**
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## Planned features
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Here is a list of all the cool stuff this library could provide one day.
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* **Simple State estimation** based on the integration of the drone odometry.
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* **Extended Kalman Filter** leveraging the onboard tag detection as the observation source
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for an Extended Kalman Filter. This provides much more stable and usable state estimate.
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* **PID Controler** to autonomously control the drone position.
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* **Visual motion estimation** estimates motion from visual image processing.
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## Usage
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```
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var client = require('ar-drone').createClient();
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var autonomy = require('autonomy').stateEstimate(client);
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autonomy.on('positon', function(position) {
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console.log('Estimated position: %j', position);
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});
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```
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## License
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The MIT License
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Copyright (c) 2013 by Laurent Eschenauer <laurent@eschenauer.be>
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
|
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furnished to do so, subject to the following conditions:
|
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|
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
|
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.
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var autonomy = exports;
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exports.StateEstimator = require('./lib/StateEstimator');
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exports.estimateState = function(client, options) {
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var estimator = new autonomy.StateEstimator(client, options);
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return estimator;
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}
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var EventEmitter = require('events').EventEmitter;
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var util = require('util');
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module.exports = StateEstimator;
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util.inherits(StateEstimator, EventEmitter);
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function StateEstimator(client, options) {
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EventEmitter.call(this);
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options = options || {};
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this._options = options;
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this._client = client;
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this._delta_t = options.delta_t || StateEstimator.DELTA_T;
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this._state = {roll: 0, pitch: 0, yaw: 0, x: 0, y: 0, z: 0};
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this._mode = options.mode || "yaw";
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if (this._client == null) throw new Error("This won't work if you don't pass a proper ardrone client.");
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console.log('State estimator initialized in %s mode.', this._mode);
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this._bind();
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}
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StateEstimator.DELTA_T = 1 / 15; // In demo mode, 15 navdata per second
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StateEstimator.prototype.state = function() {
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return this._state;
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}
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StateEstimator.prototype._bind = function() {
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var self = this;
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this._client.on('navdata', function(data) {
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self._processNavData(data);
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});
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}
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StateEstimator.prototype._processNavData = function(data) {
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var pitch = data.demo.rotation.pitch.toRad()
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, roll = data.demo.rotation.roll.toRad()
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, yaw = data.demo.rotation.yaw.toRad()
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, mag = data.magneto.heading.fusionUnwrapped.toRad()
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, vx = data.demo.velocity.x / 1000 //We want m/s instead of mm/s
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, vy = data.demo.velocity.y / 1000
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, vz = data.demo.velocity.z / 1000
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, alt = data.demo.altitude
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, dt = this._delta_t;
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;
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var phi = (this._mode == "magneto" && mag != null) ? mag : yaw;
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this._state.x = this._state.x + dt * (vx * Math.cos(phi) - vy * Math.sin(phi));
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this._state.y = this._state.y + dt * (vx * Math.sin(phi) + vy * Math.cos(phi));
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this._state.z = alt;
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this._state.roll = roll;
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this._state.pitch = pitch;
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this._state.yaw = yaw;
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this.emit('state', this._state);
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};
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/** Converts numeric degrees to radians */
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if (typeof(Number.prototype.toRad) === "undefined") {
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Number.prototype.toRad = function() {
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return this * Math.PI / 180;
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}
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}
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@@ -0,0 +1,22 @@
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{
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"name": "ardrone-autonomy",
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"version": "0.1.0",
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"description": "Building blocks for autonomous flying an AR.Drone.",
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"repository": {
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"type": "git",
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"url": "git@github.com:eschnou/ardrone-autonomy.git"
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},
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"keywords": [
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"drone",
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"ardrone",
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"nodecopter",
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"parrot",
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"autonomous",
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"kalman",
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"pid"
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],
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"dependencies": {
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},
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"author": "Laurent Eschenauer <laurent@eschenauer.be>",
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"license": "MIT"
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}
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