Sökning: "robot manipulation planning"

Visar resultat 1 - 5 av 13 avhandlingar innehållade orden robot manipulation planning.

  1. 1. Robot Manipulation Planning Among Obstacles: Grasping, Placing and Rearranging

    Författare :Joshua Alexander Haustein; Danica Kragic; Kostas E. Bekris; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; robot manipulation planning; sampling-based planning; fingertip grasp planning; placement planning; rearrangement planning; Computer Science; Datalogi;

    Sammanfattning : This thesis presents planning algorithms for three different robot manipulation tasks: fingertip grasping, object placing and rearranging. Herein, we place special attention on addressing these tasks in the presence of obstacles. LÄS MER

  3. 2. Representation and Learning for Robotic Grasping, Caging, and Planning

    Författare :Johannes Andreas Stork; Danica Kragic; Wolfram Burgard; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Grasping; Caging; Planning; State Representation; Optimization; Topology; Manipulation; Reinforcement Learning; Datalogi; Computer Science;

    Sammanfattning : Robots need to grasp, handle, and manipulate objects, navigate their environment, and understand the state of the world around them. Like all artificial intelligence agents, they have to make predictions, formulate goals, reason about actions, and make plans. LÄS MER

  4. 3. Robot Task Learning from Human Demonstration

    Författare :Staffan Ekvall; Danica Kragic; Marcus Vincze; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Robotics; Machine Learning; Artificial Intelligence; Computer Vision; Programming by Demonstration; Grasp Mappping; Grasp Recognition; Robot Grasping; Planning; Autonomous Robots; Computer science; Datalogi;

    Sammanfattning : Today, most robots used in the industry are preprogrammed and require a welldefined and controlled environment. Reprogramming such robots is often a costly process requiring an expert. By enabling robots to learn tasks from human demonstration, robot installation and task reprogramming are simplified. LÄS MER

  5. 4. Synergies between Policy Learning and Sampling-based Planning

    Författare :Robert Gieselmann; Florian T. Pokorny; Edward Johns; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Robotics; Reinforcement Learning; Motion Planning; Robotic Manipulation; Datalogi; Computer Science;

    Sammanfattning : Recent advances in artificial intelligence and machine learning have significantly impacted the field of robotics and led to the interdisciplinary study of robot learning. These developments have the potential to revolutionize the automation of tasks in various industries by reducing the reliance on human workers. LÄS MER

  7. 5. Multi-Agent Mission Planning

    Författare :Branko Miloradović; Alessandro Papadopoulos; Baran Curuklu; Mikael Ekström; Luis Merino; Mälardalens högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Computer Science; datavetenskap;

    Sammanfattning : Multi-Agent Systems (MASs) have been utilized in various settings and frameworks, and have thus been successfully applied in many applications to achieve different goals. It has been shown that MASs are more cost-effective as compared to building a single agent with all the capabilities a mission may require. LÄS MER