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Auflistung nach Schlagwort "Motion planning"

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  • Zeitschriftenartikel
    Full-Body Motion Planning for Humanoid Robots using Rapidly Exploring Random Trees
    (KI - Künstliche Intelligenz: Vol. 30, No. 0, 2016) Baltes, Jacky; Bagot, Jonathan; Sadeghnejad, Soroush; Anderson, John; Hsu, Chen-Hsien
    Humanoid robots with many degrees of freedom have an enormous range of possible motions. To be able to move in complex environments and dexterously manipulate objects, humanoid robots must be capable of creating and executing complex sequences of motions to accomplish their tasks. For soccer playing robots (e.g., the participants of RoboCup), the highly dynamic environment require real-time motion planning in spite of the enormous search space of possible motions. In this research, we propose a practical solution to the general movers problem in the context of motion planning for robots. The proposed robot motion planner uses a sample-based tree planner combined with an incremental simulator that models not only collisions, but also the dynamics of the motion. Thus it can ensure that the robot will be dynamically stable while executing the motion. The effectiveness of the robot motion planner is demonstrated both in simulation and on a real robot, using a variation of the Rapidly Exploring Random Tree (RRT) type of motion planner. The results of our empirical evaluation show that CONNECT works better than EXTEND versions of the RRT algorithms in simple domains, but that this advantage disappears in more obstacle-filled environments. The evaluation also shows that our motion planning system is able to find and execute complex motion plans for a small humanoid robot.
  • Zeitschriftenartikel
    Spatio-Temporally Constrained Planning for Cooperative Vehicles in a Harvesting Scenario
    (KI - Künstliche Intelligenz: Vol. 27, No. 4, 2013) Scheuren, Stephan; Stiene, Stefan; Hartanto, Ronny; Hertzberg, Joachim; Reinecke, Max
    The marion project aims at automatizing the working processes in the intralogistics and agriculture through process and motion planning of mobile cooperative machines. This paper focuses on the agricultural scenario of wheat harvest. The harvesting process with cooperative machines is a challenging task because the machines’ actions influence and constrain each other spatio-temporally. In marion, algorithms from robotics are adapted to solve the planning problem under the basic conditions of high dynamics in process execution due to yield deviation and limited communication bandwidth of the radio communication. The developed planning system generates and optimizes the overall plan for all involved cooperative machines regarding multiple criteria.