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    Automatic Reconstruction of Indoor Spaces from 3D Point Clouds
    (2022) Norman, Eric; Landgren, Lovisa; Chalmers tekniska högskola / Institutionen för elektroteknik; Zach, Christopher
    We present a new take on the unresolved challenge of automating indoor environment reconstruction from LiDAR point clouds. Utilizing point clouds as a basis for creation of BIM models yields highly accurate results and simplifies the task substantially as compared to gathering and using manual measuring methods. It is however still a time-consuming and labor intensive process for a human to draw the model using the point cloud as a mere blueprint. We therefore attempt to automate a key part of the process end to end, namely the reconstruction of polygonal room spaces. With the goal of reaching human accuracy, if not above, we attempt to automate the steps from point cloud to a 2D room-level polygonal model of a building floor. To this end research was conducted to combine some promising methods from different studies that have previously been done in the field into a modular data pipeline. The prototype uses multiple high-performing algorithms to denoise the point cloud, accurately identify planar room dividing components and finally define the room spaces as simple polygons. Our work shows that end-to-end automation of room space classification is indeed possible, although lack of objective measure of room divisions poses a yet unresolved challenge. For the purpose of full BIM model reconstruction, reliable room classification is a necessity. Our work shows a promising way of combining available methods into an automatic and robust indoor environment space reconstruction process with a high level of accuracy.
  • Post
    Digital Linearization of a Receiver Optimized for Radar
    (2022) Laurenius, Rickard; Chalmers tekniska högskola / Institutionen för elektroteknik; Eriksson, Thomas
    Linearity is an important property of radio frequency amplifiers that has implications for performance in a wide range of applications, from communications to radar. As digital hardware grows ever cheaper and more power efficient, digital techniques for improving the linearity of amplifiers have emerged as an effective replacement for older more power-hungry analogue methods. This thesis seeks to investigate the effectiveness of digital linearization techniques for post-distortion on the receiver side, and in the context of digital radar systems. The investigation has been performed by testing linearization algorithms on recorded signals using hardware typical of modern radio receiver systems. Triangular chirp signals and combined two-tone signals using frequency pairs based on coprime integers are shown to be effective calibration signals. Post-distortion techniques using either memoryless polynomials, memory polynomials or generalized memory polynomials are shown to suppress intermodulation distortion by up to 20dB, and to remain stable for a temperature drift of about 10C. The coefficient estimation algorithm is shown to find inverse models that can improve linearity using only a small number of samples, indicating the possibility of implementations using a low amount of digital resources and model complexities. Ways of compensating for temperature drift have been investigated but to inconclusive results.
  • Post
    Techno-Economic assessment of battery energy storage system in microgrids with the potential for energy sharing
    (2022) Sivakumar, Gopalakrishnan; Chalmers tekniska högskola / Institutionen för elektroteknik; Steen, David
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    Grasping with a mobile manipulator using 3D vision
    (2022) Chatelin, Tristan; Chalmers tekniska högskola / Institutionen för elektroteknik; Bekiroglu, Yasemin
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    Vehicle-to-Everything Optimization Considering Battery Degradation
    (2022) Bjurek, Kalle; Hagman, Victor; Chalmers tekniska högskola / Institutionen för elektroteknik; Zou, Changfu; Zou, Changfu