Abstract—Industrial robots (IR) is a popular and perspective technological equipment of modern, complex automation of production processes, which characterized by high precision, speed and flexibility of technological operations. The coordination of robotic end-effectors (EF) provided by advanced automation control systems working on IR and using various sensors and software. The main tasks of IR control systems, which realized in software, include the design of work areas of technological equipment (TE) interaction, planning and on/off line control of IR effectors movements, configuration and synchronization interaction with the TE, human safety control and so on.
The forming of complex approach to solve all of these tasks is of great interest and should take into account the systematization of information about conditions and the complexity of operations, ways of system control and software realizations. Similar approaches are implemented in popular software for IR, such as KUKA Sim, ABB RobotStudio SprutCAM, Octopus, RoboDK etc. which supports C# -similar languages. At the same time, the problem of effective effectors motion planning in the implementation for continuous trajectory (welding, milling) and discrete, defined among reference points (manipulation, assembly) is not fully solved and often in the real workspace relies on engineering experience. The creation or revision of typical PTP-moving algorithms can take into account such procedures as minimizing time and energy consumption for IR maneuvering abilities and realize it in a short computing time. This article considers the possible methodology approach to plan the IR trajectories in a complex environment.
Index Terms—Robotic, trajectory, planning, optimization, energy consumption, genetic algorithm.
The authors are with Automation and Computer-Integrated Technologies, Zhytomyr State Technological University, Zhytomyr, Ukraine (e-mail: martin.bogdanovskiy@gmail.com).
[PDF]
Cite: Industrial Robots Trajectories Planning for Flexible Manufacturing Systems, "Martin Bogdanovskyi and Josef Černohorský," International Journal of Modeling and Optimization vol. 7, no. 5, pp. 270-274, 2017.
