Sirvi Autor "Hult, Carl Hjalmar Love" järgi

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SurfMotion: An Open Source Pipeline for Robotic Pipe Cutting and Welding
(Tartu Ülikool, 2025) Hult, Carl Hjalmar Love; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Robotic pipe cutting and welding are examples of precise surface-conforming tasks for manipulator robots. Though they are commonplace industrial processes, they pose difficult technical challenges, particularly in motion planning and execution on complex geometries. Existing solutions are largely proprietary, expensive, and closely tied to specific hardware platforms, while open-source alternatives are limited in scope and integration. This thesis introduces SurfMotion, a ROS package developed to begin to bridge the gap between open-source and proprietary solutions for surface-conforming robotic tasks. SurfMotion provides a modular pipeline for generating, projecting and executing geometry-aware Cartesian trajectories on complex surfaces. The package integrates surface processing, path projection, inverse kinematics feasbility checking, and robot-agnostic trajectory execution, leveraging the ROS 2 and MoveIt frameworks. The effectiveness of SurfMotion is demonstrated and quantified in terms of Cartesian space error, velocity consistency, and overall smoothness of motion execution through simulated robotic cutting and welding tasks across four example robot models (UR5, UR20, Fanuc m10ia and Kuka iiwa14). Experimental results show that two of the MoveIt motion execution frameworks integrated achieve sub-millimeter accuracy in path tracking.
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Using and evaluating the real-time spatial perception system hydra in real-world scenarios
(Tartu Ülikool, 2023) Hult, Carl Hjalmar Love; Kruusamäe, Karl, juhendaja
Hydra is a real-time machine perception system released open source in 2022 as a package for Robot Operating System (ROS). Machine perception systems like Hydra may play a role in the engineering of the next generation of spatial AIs for autonomous robots. Hydra is in the preliminary stages of its existence and does not come with intrinsic support for running on custom datasets. This thesis primarily aims to find out whether the promised capabilities of Hydra can be replicated. As well as to establish a workflow and guidelines for what modifications to Hydra are needed to successfully run it.