GERAÇÃO DE TRAJETÓRIAS SUAVES COM POLINÔMIOS DE QUINTA ORDEM E INTELIGÊNCIA ARTIFICIAL, SISTEMAS EVOLUTIVOS APLICADOS A UMA JUNTA DE BRAÇO ROBÓTICO: RESULTADOS EM AMBIENTE SIMULADO

• DOI: https://doi.org/10.22533/at.ed.450112505061

• Palavras-chave: Planejamento de trajetória, polinômios de quinta ordem, algoritmos genéticos, braço robótico, simulação robótica

• Keywords: Trajectory Planning, Fifth-Order Polynomials, Genetic Algorithms, Robotic Arm, Robotic Simulation.

• Abstract: Robotics is an interdisciplinary field of engineering dedicated to developing systems capable of performing tasks with full or partial autonomy. Among the main challenges of autonomous robotics is trajectory planning, which determines safe, feasible, and optimized paths for robots to move through diverse environments. This task requires accounting for multiple variables, such as the environment’s topology, the robot’s kinematic and dynamic constraints, and operational safety requirements. The most widely used methods include potential-field–based algorithms, which employ cost functions to guide motion along energy gradients, and search algorithms, such as A* and Dijkstra, which systematically explore the state space until a viable solution is found. Both approaches have advantages and limitations regarding computational efficiency, robustness, and adaptability. Trajectory planning is a continually evolving research area. It is fundamental to advancing critical applications such as industrial robots (assembly, welding, painting), robot-assisted medical systems (minimally invasive surgeries), and autonomous mobile robotics (ground, aerial, and underwater vehicles). Current trends point to integration with real-time perception and artificial intelligence techniques to cope with dynamic and uncertain environments.