The paper describes the simulation environment for the autonomous battery management system for drones called Droneport. First, the problem of battery management is briefly described, and specific experimental and commercial solutions are listed. Then the concept of the proposed Droneport system is described. The next section is fully dedicated to the description of the individual components of the simulation: simulation of the drone, Droneport, the outer environment, and the traffic controller. The function of the individual components is illustrated by the example of two drones performing a predefined mission.
The paper describes the 3-dimensional trajectory planning editor which supports the consequent real-time generation of the robot effector path using motion control technology (PLCopen standard). The presented 3D editor is powered by modern open technologies and enables users to simply view, edit and simulate the final trajectory. Moreover, the role of the editor in the whole robot control chain is clearly explained and demonstrated on 3D cable robot example.
The popularity of using vertical take-off and landing unmanned aerial systems continues to rise. Although the use of these devices seems to be almost limitless, the main drawback is still the battery capacity and the need to replace or recharge it several times per hour. This article provides a technical overview of the development of an experimental mechatronic system for automatic drone battery management called Droneport. It was developed as a system with a landing platform, automatic battery exchange and recharging outside the drone, allowing a quick return to the mission. The first part presents its mechanical design, installed instrumentation and software environment. The next part is devoted to the description of the individual hardware components, highlighting the specific problems that had to be solved to optimize size, weight and robustness requirements. The final section summarizes our observations regarding the contribution of this tool to the autonomy of drones or UAVs in general.
The paper deals with a lead-through method of programming for industrial robots. The goal is to automatically reproduce 6DoF trajectories of a tool wielded by a human operator demonstrating a motion task. We present a novel motion-tracking system built around the HTC Vive pose estimation system. Our solution allows complete automation of the robot teaching process. Specific algorithmic issues of system calibration and motion data post-processing are also discussed, constituting the paper’s theoretical contribution. The motion tracking system is successfully deployed in a pilot application of robot-assisted spray painting.
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