D-type shaft is widely used in precision machinery products such as motors and intelligent robots. The straightness of the D-type shaft is an important factor influencing its machining accuracy and dynamic performance, which is normally improved by the three-point pressure straightening process. This paper proposes a general stroke-based model to predict the relevant parameters for the straightening process of D-type shaft, considering the bending deformations in three dimensions. The distribution of stress and strain inside the D-type shaft during the straightening process in arbitrary position of the cross section and the bending moment are analyzed by using linear hardening material model. The relationship between deflection and the internal stress on the loading position is explored, and a straightening stroke model of D-type shaft is obtained. The correctness of the stroke-based straightening model has been validated by finite element method (FEM) simulation analysis and bending experiments. The results show that the proposed model can improve the accuracy and efficiency of the D-type shaft straightening process. Furthermore, it provides a novel method for the modelling of the straightening process regarding the special shaped bar stock.

Reinforcement learning (RL) has great potential for skill acquisition in robotic disassembly, but the process in real-world scenarios remains inefficient. In response, we present an efficient RL-based method for acquiring disassembly skills, incorporating relevant external knowledge to enhance learning performance. This method aims at a rapid and stable acquisition of disassembly skills which cable with transferability. The successful disassembly of various types of clearance-fit components highlights the practical applicability of the method. In this content, we design both control policies and reward functions according to the disassembly knowledge to guide and optimize the RL process. Our findings indicate that augmenting RL with external knowledge not only enhances learning efficiency, but also significantly improves skill performance. Comparative evaluations of disassembly skills obtained by different methods on the same tasks demonstrate that the proposed method yields skills with better transferability. Additionally, the method outlined is adaptable and can be implemented with various RL algorithms, making it a robust solution for enhancing robotic disassembly operations.

Disassembly is a crucial step in remanufacturing and is currently mainly performed by humans. Automating disassembly can reduce labour costs and make remanufacturing more economically attractive. This paper focuses on identifying and characterizing a common disassembly task, dual peg-hole disassembly, with the aim of building a robotic disassembly system for this task. We enumerate the possible contact states and their geometric conditions during the extraction of two studs in a dual peg-hole. This paper focuses on jamming in the extraction and conducts geometrical and quasi-static analyses to determine the boundary conditions of jamming. Based on the analyses, this paper also investigates the role of active compliance as a solution to avoid jamming. We also simulate critical variables and examine key parameters such as the degree of compliance, the location of the compliance centre and initial position errors. Finally, we conduct experimental studies on dual peg-hole extraction with different compliance centres obtained using active compliance.

As an important form of additive manufacturing, welding is widely used in steel components welding work of construction, shipbuilding and other fields. In this study, an intelligent welding path generation algorithm based on multi-section interpolation is proposed in order to deal with non-standard multi-pass welding grooves which are difficult to be handled by automatic welding equipment in the construction site. Firstly, the non-standard grooves are classified and the reasons for their occurrence are discussed. Secondly, an automatic welding additive manufacturing system framework is discussed and an appropriate detection method is selected. Then, combining with the welding standard of non-standard grooves and the characteristics of the welding process, a multi-section interpolation-based welding path generation algorithm is proposed. Finally, a visual experiment platform was built to detection the typical non-standard groove and the welding experiment is implemented to verify the feasibility of the algorithm. According to the path generated by the algorithm, the welded steel components test plate meets the actual engineering standard after quality inspection. The experimental results and simulation results conclude the algorithm can be used to generate the welding path of the non-standard groove.