In order to solve the problem that noise detection inside a cabin is difficult due to the complexity and narrow space, a local space planning method of a manipulator based on the goal-oriented rapidly-exploring random tree (RRT) algorithm is proposed.

A six-degrees-of-freedom (6-DOF) manipulator is used as the carrier, and a fixture is installed at the end of the manipulator. The four fixed points inside the cabin are used as the reference points to study the mechanical arm in the local space. The trajectory planning is traversed and the reference point-1 is taken as an example to measure the noise of its 6 measurement surfaces and 147 measurement points. The noise signal and the position and attitude information of the space to be measured are matched and analyzed, and the environmental noise of the current measurement point is fed back to form a sound pressure cloud map.

The experimental results show that the robotic arm can realize trajectory planning and noise measurement for all measurement points corresponding to the four reference points without collision.

The proposed method has practical value in being able to realize intelligent planning and internal noise detection in narrow cabin areas.