This homework consists of two state estimation problems. In the first problem, you will implement a Kalman Filter to estimate the position of 2D landmarks as a robot navigates through its environment. In the second problem, you will implement an Extended Kalman Filter to estimate the pose of the robot as it navigates through its environment and receives measurements of known 2D landmarks. All starter code is provided in Google Colab, and all answers should be compiled in a PDF a submitted via gradescope.
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This homework consists of two problems. In the first problem, you will gain exposure to PyTorch and the use of pretrained neural network models applied to a computer vision task (Object Detection). In the second problem, you will implement an algorithm for robotic exploration. Please read the homework carefully. All starter code is provided in Google Colab, and all answers should be compiled in a PDF a submitted via gradescope.
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The goal of this homework is to familiarize you with computer vision algorithms for camera calibration, image processing, and feature extraction. Please read the homework carefully.
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The goal of this homework is to familiarize you with algorithms for path planning in constrained environments (e.g. in the presence of obstacles) and techniques to integrate planning with trajectory generation and control. Please read the homework carefully.
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The goal of this homework is to familiarize you with some of the techniques for controlling nonholonomic wheeled robots. Please read the homework carefully.
Feel free to use this Latex template.