A Comparison Between the Particle Swarm and the Newton-Raphson Algorithms for Solving the Inverse Kinematics Problem in a 4-DOF Robotic Arm

• Jaqueline Cavaller Faino Unioeste
• Josué Pereira de Castro Unioeste
• Adriana Postal Unioeste
• Marcio Seiji Oyamada Unioeste

Resumo

Solving the inverse kinematics problem of a manipulator robot is one of the main concerns of industrial robotics, since it involves solving nonlinear equations that may have no, one or several solutions. This problem has typically been solved using traditional methods such as iterative numerical algorithms, which have proved to be computationally costly. This prompted researchers to investigate alternative approaches to this problem, and the most commonly used nowadays are artificial intelligence and combinatorial optimization algorithms. With this in mind, this paper presents a study that investigated the use of the particle swarm optimization algorithm to solve the inverse kinematics problem of a robotic manipulator and compared its results with those of the Newton-Raphson algorithm. This led to the conclusion that although the particle swarm optimization is not superior to the Newton-Raphson algorithm in terms of time and memory, it provides more accurate and reliable results.

Palavras-chave: Accuracy, Nonlinear equations, Service robots, Kinematics, Manipulators, Reliability, Time factors, Particle swarm optimization, Newton method, Optimization, robotics, kinematics, inverse kinematics, automation