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This paper presents an evolutionary approach to multi-objective path planning. The paths are defined on continuous scenes with disjoint and/or non-convex obstacles, for robots moving towards their destinations along linearly piecewise trajectories with any number of vertices. The fastest feasible route is genetically selected via a simultaneous minimization of path length and path steering angle....
Battery fast charging is a crucial issue in both research and application to realize and promote the mass commercialization of electric vehicles, especially pure electric vehicles. However, due to the strong nonlinear properties of batteries, the charging process should take into consideration various factors such as state of charge (SoC), temperature, and charging current, so as to assure the safety,...
This work aims to develop an artificial intelligence for a helicopter pilot. That is, a system that learns to fly a helicopter the way a human pilot would. It draws on the benefits of using inverse simulation and genetic algorithms to model systems similar to human process. The goal is to define tasks for the helicopter and have the pilot find control settings that carry out those tasks. The inverse...
This work presents a solution to solve industrial cranes kinematic control problem also called automatic travel control (ATC) [10]. Aspects such as optimal trajectory reference calculation considering: process cycle time and distance travelled minimization, improvements in mechanical transmission systems useful life, prohibited areas and obstacles in the crane workspace, etc., and load position control...
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