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So long you have a sensor to read the angle of the steering wheel, you can use the bicycle kinematic model to compute odometry for an Ackermann drive platform, e.g. a car: $$ \begin{align} \\ \dot{x} & = v \; cos(\psi + \beta) \\ \\ \dot{y} & = v \; sin(\psi + \beta) \\ \\ \dot{\psi} & = \frac{v}{l_r} sin(\beta) \\ \\ \beta & = tan^{-1} \...


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In order to transform encoder signals to robot motions a kinematic model of the robot is needed. In some cases this is very simple, just including the gear ratios and a heading angle (e.g. with Ackerman steering model). This is a simple kinematic model. A more complex case is differential steering, where the encoder signals pass through a kinematic ...


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Your noise term for the KF needs to reflect how you expect the true propagation of the state will differ from your model of the propagation. For example, the acceleration uncertainty is 1 while your true uncertainty is drawn from a uniform distribution of [-10,10]. I altered your code so the KF is now using the IMU information within the propagation step. ...


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DSO initializes the scene and camera poses with a specific scale factor such that the average inverse depth of the pointHessians is one. After the initialization the first two frameHessians are led into the backend to do a bundle adjustment like optimization in which, however, the previous determined scale can change (because the absolute scale is not ...


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