//////////////////////////////////////////////////////////////////////////// // // This file is part of RTIMULib-Teensy // // Copyright (c) 2014-2015, richards-tech // // Permission is hereby granted, free of charge, to any person obtaining a copy of // this software and associated documentation files (the "Software"), to deal in // the Software without restriction, including without limitation the rights to use, // copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the // Software, and to permit persons to whom the Software is furnished to do so, // subject to the following conditions: // // The above copyright notice and this permission notice shall be included in all // copies or substantial portions of the Software. // // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, // INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A // PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT // HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION // OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE // SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. #ifndef _RTFUSIONKALMAN4_H #define _RTFUSIONKALMAN4_H #include "RTFusion.h" class RTFusionKalman4 : public RTFusion { public: RTFusionKalman4(); ~RTFusionKalman4(); // fusionType returns the type code of the fusion algorithm virtual int fusionType() { return RTFUSION_TYPE_KALMANSTATE4; } // reset() resets the kalman state but keeps any setting changes (such as enables) void reset(); // newIMUData() should be called for subsequent updates // deltaTime is in units of seconds void newIMUData(RTIMU_DATA& data, const RTIMUSettings *settings); // the following two functions can be called to customize the covariance matrices void setQMatrix(RTMatrix4x4 Q) { m_Q = Q; reset();} void setRkMatrix(RTMatrix4x4 Rk) { m_Rk = Rk; reset();} private: void predict(); void update(); RTVector3 m_gyro; // unbiased gyro data RTFLOAT m_timeDelta; // time between predictions RTQuaternion m_stateQ; // quaternion state vector RTQuaternion m_stateQError; // difference between stateQ and measuredQ RTMatrix4x4 m_Kk; // the Kalman gain matrix RTMatrix4x4 m_Pkk_1; // the predicted estimated covariance matrix RTMatrix4x4 m_Pkk; // the updated estimated covariance matrix RTMatrix4x4 m_PDot; // the derivative of the covariance matrix RTMatrix4x4 m_Q; // process noise covariance RTMatrix4x4 m_Fk; // the state transition matrix RTMatrix4x4 m_FkTranspose; // the state transition matrix transposed RTMatrix4x4 m_Rk; // the measurement noise covariance // Note: SInce Hk ends up being the identity matrix, these are omitted // RTMatrix4x4 m_Hk; // map from state to measurement // RTMatrix4x4> m_HkTranspose; // transpose of map }; #endif // _RTFUSIONKALMAN4_H