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This paper presents a new approach for geometrically constrained path planning applied to the field of robotic grasping. The method proposed in this paper is based on the Fast Marching Square (FM
) and a path calculation approach based on an optimization evolutionary filter named Differential Evolution (DE). The geometric restrictions caused by the link lengths of the kinematic chain composed by the robot arm and hand are introduced in the path calculation phase. This phase uses both the funnel potential of the surroundings created with FM
and the kinematic constraints of the robot as cost functions to be minimized by the evolutionary filter. The use of an optimization filter allows for a near-optimal solution that satisfies the kinematic restrictions, while preserving the characteristics of a path computed with FM
. The proposed method is tested in a simulation using a robot composed by a mobile base with two arms.
The localization problem in mobile robotics can be defined as the search of the robot's coordinates in a known environment. If there is no information about the initial location, we are talking about global localization. In this work, we have developed an algorithm that solves this problem in a three-dimensional (3D) environment using evolutionary computation concepts. The method has been called RELF-3D and has many features that make it very robust and reliable: thresholding and discarding mechanisms, different cost functions, effective convergence criteria, and so on. The resulting global localization module has been tested in numerous experiments and the most important improvement obtained is the accuracy of the method, allowing its application in manipulation tasks.
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