... | ... | @@ -258,11 +258,11 @@ We would have attempted to amend the inaccurate angle calculation and then use t |
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Firstly, we should note that we were far from completing our goal of finishing the exercises within five hours. We will take this into account in the following lessons, either by allotting more time or by planning the exercises in more detail and sticking to a stricter plan.
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Using Hurbain's three suggestions for optimizing the conditions for the robot to act in resulted in one particular main insight that could be especially useful later, which is that the calibration angle has significant impact on the robot's ability to balance and must take into account the weight distribution of the robot's physical appearance.
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Using Hurbain's three suggestions for optimizing the conditions for the robot to act in resulted in one particular main insight that could be especially useful later, which is that the calibration angle has significant impact on the robot's ability to balance and must take into account the weight distribution of the robot's physical appearance. Later experiments with the PID paramters also showed the significant influence that the these have on the robot's ability to respond to physical conditions.
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Our experimentation with creating a balancing robot using the light sensor proved to be immensely difficult. Systematically attempting different values for our P, I, D and setpoint variables proved somewhat fruitful, as we managed to somewhat remedy some of the issues that appeared to be causing the robot to fall over, but in the end it was still unable to balance for more than a second or two at best. A big culprit leading to this was also the mysterious random stopping of the motors that we were unable to find the source of.
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Testing the parameters in a way inspired by grid search provided us with a structured approach to investigating how the different paramters influence each other. Although limited time forced us to move on before fully completing an actual grid search, we did obtain some insights into the effect of the parameters on the robot's responsiveness to the light sensor.
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Testing the parameters in a way inspired by grid search provided us with a structured approach to investigating how the different paramters influence each other. Although limited time forced us to move on before fully completing an actual grid search, we did obtain some insights into the effect of the parameters on the robot's responsiveness to the light sensor.
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Our experimentation with creating a balancing robot using the light sensor proved to be immensely difficult. Systematically attempting different values for our *p*, *i*, *d* and setpoint variables proved somewhat fruitful, as we to some extend managed to remedy some of the issues that appeared to be causing the robot to fall over, but in the end the robot was still unable to balance for more than a second or two at best. A big culprit leading to this was also the mysterious random stopping of the motors that we were unable to find the source of.
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We observed that changes in the angle reflected less strongly in the readings of the color sensor than in those of the light sensor. Our test of this underlined the necessity of interleaving qualitative assessments with quantitative measurements, due to the difficulty of conducting isolated experiments - many different factors influence the results and can sometimes be hard to take into account.
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