<p>In view of the poor generalization and inefficiency of the general traditional methods in solving the inverse kinematics of industrial robots, an inverse kinematics solving method based on the improved flow direction algorithm is proposed. We apply the Levy flight strategy to the global search strategy to locate the optimal solution quickly. In order to avoid getting stuck in the local optimum, the local search using the self-updating method deeply exploits the information surrounding the optimal solution to explore a better solution. Inverse kinematics solution is then performed. Improvements to the algorithm are made to give the flow direction algorithm better search performance and to avoid the algorithm falling into a local optimum. Meanwhile, the traditional inverse kinematics is transformed into a multi-objective optimization problem with the objectives of minimizing robot energy consumption and minimizing the end-effector position error. Through comparative experiments, it is known that the improved flow direction algorithm has high convergence accuracy and higher solving efficiency.</p> Graphical abstract <p>Inverse kinematics solution framework based on improved flow direction algorithm</p>