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This paper aims to present a set of processes for obtaining the global spraying trajectory of a cold spraying robot on a complex surface.

The complex workpiece surfaces in the project are first divided by triangular meshing. Then, the geodesic curve method is applied for local path planning. Finally, the subsurface trajectory combination optimization problem is modeled as a GTSP problem and solved by the ant colony algorithm, where the evaluation scores and the uniform design method are used to determine the optimal parameter combination of the algorithm. A global optimized spraying trajectory is thus obtained.

The simulation results show that the proposed processes can achieve the shortest global spraying trajectory. Moreover, the cold spraying experiment on the IRB4600 six-joint robot verifies that the spraying trajectory obtained by the processes can ensure a uniform coating thickness.

The proposed processes address the issue of different parameter combinations, leading to different results when using the ant colony algorithm. The two methods for obtaining the optimal parameter combinations can solve this problem quickly and effectively, and guarantee that the processes obtain the optimal global spraying trajectory.

This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of nodes and deploy in free space for reliable trajectory planning.

Traditional PRM is modified by developing a decision-making strategy for the selection of optimal nodes w.r.t. the complexity of the environment and deploying the optimal number of nodes outside the closed segment. Subsequently, the generated trajectory is made smoother by implementing the modified Bezier curve technique, which selects an optimal number of control points near the sharp turns for the reliable convergence of the trajectory that reduces the sum of the robot’s turning angles.

The proposed technique is compared with state-of-the-art techniques that show the reduction of computational load by 12.46%, the number of sharp turns by 100%, the number of collisions by 100% and increase the velocity parameter by 19.91%.

The proposed adaptive technique provides a better solution for autonomous navigation of unmanned ground vehicles, transportation, warehouse applications, etc.

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

This paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.

The gender-gap reversal in education could have far-reaching consequences for marriage and family lives in the United States. This study seeks to address the following question: As women increasingly marry men with less education than they have themselves, is the traditional male breadwinner model in marriage challenged?

This study takes a life course approach to examine how educational assortative mating shapes trajectories of change in female breadwinning status over the course of marriage. It uses group-based trajectory models to analyze data from the National Longitudinal Survey of Youth 1979.

The results reveal substantial movement by wives in and out of the primary breadwinner role across marital years and great heterogeneity in female breadwinning trajectories across couples. In addition, educational assortative mating plays a role in shaping female breadwinning trajectories: Compared with wives married to men whose educational levels equal or exceed their own, wives married to men with less education than themselves are more likely to have a continuously high probability of being primary earners and are also more likely to gradually or rapidly transition into primary earners if initially they are not.

This study examines couples’ breadwinning arrangements over an extended period of time and identifies qualitatively distinct patterns of change in female breadwinning that are not readily identifiable using ad hoc, ex ante classification rules. The findings suggest that future research on the economics of marriage and couple relations in families would benefit from a life course approach to conceptualizing couples’ dynamic divisions of breadwinning.

Imitation learning is a powerful tool for planning the trajectory of robotic end-effectors in Cartesian space. Present methods can adapt the trajectory to the obstacle; however, the solutions may not always satisfy users, whereas it is hard for a nonexpert user to teach the robot to avoid obstacles in time as he/she wishes through demonstrations. This paper aims to address the above problem by proposing an approach that combines human supervision with the kernelized movement primitives (KMP) model.

This approach first extracts the reference database used to train KMP from demonstrations by using Gaussian mixture model and Gaussian mixture regression. Subsequently, KMP is used to modulate the trajectory of robotic end-effectors in real time based on feedback from its interaction with humans to avoid obstacles, which benefits from a novel reference database update strategy. The user can test different obstacle avoidance trajectories in the current task until a satisfactory solution is found.

Experiments performed with the KUKA cobot for obstacle avoidance show that this approach can adapt the trajectories of the robotic end-effector to the user’s wishes in real time, including trajectories that the robot has already passed and has not yet passed. Simulation comparisons also show that it exhibits better performance than KMP with the original reference database update strategy.

An interactive learning approach based on KMP is proposed and verified, which not only enables users to plan the trajectory of robotic end-effectors for obstacle avoidance more conveniently and efficiently but also provides an effective idea for accomplishing interactive learning tasks under constraints.

This contribution introduces sequence analysis to higher education research, an explorative technique aiming at detecting patterns, regularities and resemblance in time-ordered data. Thereby, it enables a holistic perspective on over-time developments and processes such as educational pathways or academic careers. In this contribution, the foundations and general logic of sequence analysis will be described. As an example, referring to the life course as a framing paradigm, sequence analysis is applied to reconstruct the study trajectories of a cohort of bachelor students in Germany. The potential of sequence analysis in three specific higher education research areas is outlined, that is, to study post-secondary education trajectories, academic careers and the development trajectories of higher education organizations. The conclusion discusses advantages and disadvantages, challenges and practicalities.

Collaboration and acquisition have traditionally been observed as two alternative strategies when accessing external technologies. However, real option scholars have recently argued that firms can also engage in transitional technology sourcing trajectories where collaboration and acquisition are used as complementary strategies. While these real option scholars have identified factors that influence when partners are likely to shift from collaboration to acquisition, they remain silent on how such a transition can be effectively managed. Based on a multiple case study of four transitional technology sourcing trajectories between one new entrepreneurial and one established firm, this study therefore explores how the pre-acquisition collaboration stage and the post-acquisition integration are related to each other. Findings suggest that entrepreneurial companies may use the pre-acquisition collaboration stage as a period to evaluate the goodwill of the established partner. In addition, we point to the presence of pre-acquisition integration efforts and the extent of strategic convergence during the pre-acquisition collaboration stage as factors that substantially influence the success of the post-acquisition integration process in transitional governance trajectories.

The purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction motion.

A trajectory error compensation method based on admittance-extended Kalman filter (AEKF) error fusion for human–exoskeleton interaction control. The admittance controller is used to calculate the trajectory error adjustment through the feedback human–exoskeleton interaction force, and the actual trajectory error is obtained through the encoder feedback of exoskeleton and the designed trajectory. By using the fusion and prediction characteristics of EKF, the calculated trajectory error adjustment and the actual error are fused to obtain a new trajectory error compensation, which is feedback to the knee exoskeleton controller. This method is designed to be capable of improving the trajectory tracking performance of the knee exoskeleton and enhancing the compliance of knee exoskeleton interaction.

Six volunteers conducted comparative experiments on four different motion frequencies. The experimental results show that this method can effectively improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction.

The AEKF method first uses the data fusion idea to fuse the estimated error with measurement errors, obtaining more accurate trajectory error compensation for the knee exoskeleton motion control. This work provides great benefits for the trajectory tracking performance and compliance of lower limb exoskeletons in human–exoskeleton interaction movements.

Research on same-sex marriage has suggested that the transition to marriage is a symbolically meaningful experience that significantly changes sexual minority lives. This chapter draws upon semi-structured, in-depth interviews with 28 married gay men and lesbians to examine how the life course trajectories they took en route to marriage shaped their experiences transitioning to marriage. A description of the short and direct and long and winding trajectories to marriage is provided. Subsequently, it is demonstrated that, although those who took the former report experiences much like those documented by research thus far, those who took the latter had smaller wedding ceremonies to which they attach relatively little meaning, and they report that getting married has done little to change their family relationships. These findings paint a more nuanced picture of the transition to same-sex marriage than has been documented to-date, and point to important directions for future research.