16 citations · 36 across the 3 of their papers we have counts for
5 papers
Efficient task and path planning for maintenance automation using a robot system
Christian Friedrich, Akos Csiszar, Armin Lechler +1
The research and development of intelligent automation solutions is a ground-breaking point for the factory of the future. A promising and challenging mission is the use of autonom…
Maintenance automation: methods for robotics manipulation planning and execution
Christian Friedrich, Ralf Gulde, Armin Lechler +1
Automating complex tasks using robotic systems requires skills for planning, control and execution. This paper proposes a complete robotic system for maintenance automation, which…
Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task
Thomas Reichenbach, Johannes Clar, Andreas Pott +1
This paper presents a method for dynamic adjustment of cable preloads based on the actuation redundancy of \acp{CDPR}, which allows increasing or decreasing the platform stiffness…
Deep Reinforcement Learning using Cyclical Learning Rates
Ralf Gulde, Marc Tuscher, Akos Csiszar +2
Deep Reinforcement Learning (DRL) methods often rely on the meticulous tuning of hyperparameters to successfully resolve problems. One of the most influential parameters in optimiz…
Reinforcement Learning Approach to Vibration Compensation for Dynamic Feed Drive Systems
Ralf Gulde, Marc Tuscher, Akos Csiszar +2
Vibration compensation is important for many domains. For the machine tool industry it translates to higher machining precision and longer component lifetime. Current methods for v…