Abstract
The paper deals with the generation of optimal trajectories for industrial robots in machining and additive manufacturing applications. The proposed method uses an Ant Colony algorithm to solve a kinodynamic motion planning problem. It exploits the kinematic redundancy that is often present in these applications to optimize the execution of trajectory. At the same time, the robot kinematics and dynamics constraints are respected and robot collisions are avoided. To reduce the computational burden, the task workspace is discretized enabling the use of efficient network solver based on Ant Colony theory. The proposed method is validated in robotic milling and additive manufacturing real-world scenarios.
Highlights
The growing demand for advanced industrial robotic applications such as machining and additive manufacturing highlights the importance of motion planning algorithms in this field [1,2].As a consequence of this trend, a strong effort has been put into the improvement of the algorithm efficiency, especially in terms of reduction of the computing time
This work proposes a unified framework to deal with kinodynamic motion planning applied to machining, welding, gluing, and additive manufacturing tasks
To solve the discrete motion planning problem, we propose a modified Ant Colony Optimization algorithm
Summary
The growing demand for advanced industrial robotic applications such as machining and additive manufacturing highlights the importance of motion planning algorithms in this field [1,2]. Depending on the technological requirements of the specific machining task the redundant DoF/DoFs can be optimized to improve the process results [23] Another emerging field for industrial robots is represented by the additive manufacturing and laser cladding, that is, metal material deposition with techniques such as laser metal deposition or electron beam melting [24,25,26]. This work proposes a unified framework to deal with kinodynamic motion planning applied to machining, welding, gluing, and additive manufacturing tasks This allows us to cope with different technological constraints and objectives, avoiding the need of tailored solutions.
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