Planning scheme of artificial assembly posture and arm movement path in narrow space

Manual assembly in a narrow space involves problems of low efficiency and difficult assembly. In view of the lack of assembly process planning and assisted manual assembly in this kind of scenario, a hybrid modeling simulation method of human posture was proposed. This method combined the characteristics of manual assembly in narrow space. The assembly planning process was divided into two parts: trunk and lower limb posture planning and human arm movement planning, to reduce the complexity of planning and the difficulty of manual assembly. In the posture planning part, this study solved for the human trunk and lower limbs by establishing a multi-objective optimization model and achieved automatic screening of assembly posture according to the weight of each target element. Arm movement planning involved a neural network of assembly spaces to guide the sampling process of the path planner combined with the inverse solution of arm kinematics for environmental collision detection to quickly obtain a feasible collision-free arm movement path from the initial position to the assembly target. Finally, the feasibility of the method in a narrow space was verified by building a scene and carrying out the corresponding manual assembly operation experiments.