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A multi-objective approach for the motion planning of redundant manipulators
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Orientador(es)
Resumo(s)
Kinematic redundancy occurs when a manipulator possesses more degrees of freedom than those
required to execute a given task. Several kinematic techniques for redundant manipulators control the
gripper through the pseudo-inverse of the Jacobian, but lead to a kind of chaotic inner motion with
unpredictable arm configurations. Such algorithms are not easy to adapt to optimization schemes and,
moreover, often there are multiple optimization objectives that can conflict between them. Unlike single
optimization, where one attempts to find the best solution, in multi-objective optimization there is no
single solution that is optimum with respect to all indices. Therefore, trajectory planning of redundant
robots remains an important area of research and more efficient optimization algorithms are needed.
This paper presents a new technique to solve the inverse kinematics of redundant manipulators, using a
multi-objective genetic algorithm. This scheme combines the closed-loop pseudo-inverse method with a
multi-objective genetic algorithm to control the joint positions. Simulations for manipulators with three
or four rotational joints, considering the optimization of two objectives in a workspace without and with
obstacles are developed. The results reveal that it is possible to choose several solutions from the Pareto
optimal front according to the importance of each individual objective.
Descrição
Palavras-chave
Redundant manipulators Robots Kinematics Multi-objective genetic algorithms Trajectory planning
Contexto Educativo
Citação
Editora
Elsevier