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This paper aims to focus on the spatial docking task of unmanned vehicles under ground conditions. The docking task of military unmanned vehicle application scenarios has strict requirements. Therefore, how to design a docking robot mechanism to achieve accurate docking between vehicles has become a challenge.

In this paper, first, the docking mechanism system is described, and the inverse kinematics model of the docking robot based on Stewart is established. Second, the genetic algorithm-based optimization method for multiobjective parameters of parallel mechanisms including workspace volume and mechanism flexibility is proposed to solve the problem of multiparameter optimization of parallel mechanism and realize the docking of unmanned vehicle space flexibility. The optimization results verify that the structural parameters meet the design requirements. Besides, the static and dynamic finite element analysis are carried out to verify the structural strength and dynamic performance of the docking robot according to the stiffness, strength, dead load and dynamic performance of the docking robot. Finally, taking the docking robot as the experimental platform, experiments are carried out under different working conditions, and the experimental results verify that the docking robot can achieve accurate docking tasks.

Experiments on the docking robot that the proposed design and optimization method has a good effect on structural strength and control accuracy. The experimental results verify that the docking robot mechanism can achieve accurate docking tasks, which is expected to provide technical guidance and reference for unmanned vehicles docking technology.

This research can provide technical guidance and reference for spatial docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

This paper aims to explore the implications of algorithmic management on careers and employment relationships in the Nigerian gig economy. Specifically, drawing on labour process theory (LPT), this study provides an understanding of the production relations beyond the “traditional standard” to “nonstandard” forms of employment in a gig economy mediated by digital platforms or digital forms of work, especially on ride-hailing platforms (Uber and Bolt).

This study adopted the interpretive qualitative approach and a semi-structured interview of 49 participants, including 46 platform drivers and 3 platform managers from Uber and Bolt.

This study addresses the theoretical underpinnings of the LPT as it relates to algorithmic management and control in the digital platform economy. The study revealed that, despite the ultra-precarious working conditions and persistent uncertainty in employment relations under algorithmic management, the underlying key factors that motivate workers to engage in digital platform work include higher job flexibility and autonomy, as well as having a source of income. This study captured the human-digital interface and labour processes related to digital platform work in Nigeria. Findings of this study also revealed that algorithmic management enables a transactional exchange between platform providers and drivers, while relational exchanges occur between drivers and customers/passengers. Finally, this study highlighted the perceived impact of algorithmic management on the attitude and performance of workers.

The research presents an interesting case study to investigate the influence of algorithmic management and labour processes on employment relationships in the largest emerging economy in Africa.

The six-axis force/torque sensor based on a Y-type structure has the advantages of simple structure, small space volume, low cost and wide application prospects. To meet the overall structural stiffness requirements and sensor performance requirements in robot engineering applications, this paper aims to propose a Y-type six-axis force/torque sensor.

The performance indicators such as each component sensitivities and stiffnesses of the sensor were selected as optimization objectives. The multiobjective optimization equations were established. A multiple quadratic response surface in ANSYS Workbench was modeled by using the central composite design experimental method. The optimal manufacturing structural parameters were obtained by using multiobjective genetic algorithm.

The sensor was optimized and the simulation results show that the overload resistance of the sensor is 200%F.S., and the axial stiffness, radial stiffness, bending stiffness and torsional stiffness are 14.981 kN/mm, 16.855 kN/mm, 2.0939 kN m/rad and 6.4432 kN m/rad, respectively, which meet the design requirements, and the sensitivities of each component of the optimized sensor have been well increased to be 2.969, 2.762, 4.010, 2.762, 2.653 and 2.760 times as those of the sensor with initial structural parameters. The sensor prototype with optimized parameters was produced. According to the calibration experiment of the sensor, the maximum Class I and II errors and measurement uncertainty of each force/torque component of the sensor are 1.835%F.S., 1.018%F.S. and 1.606%F.S., respectively. All of them are below the required 2%F.S.

Hence, the conclusion can be drawn that the sensor has excellent comprehensive performance and meets the expected practical engineering requirements.

The purpose of this paper is to propose a strategy for the final assembly of helicopter fuselage with weak rigidity parts and mismatched jointing butt ends.

The strategy is based on path planning methods. Compared with traditional path planning methods, the configuration-space and collision detection in the method are different. The obstacles in the configuration-space are weakly rigid and allow continuous contact with the robot. The collision detection is based on interference magnitudes, and the result is divided into no collision, weak collision and strong collision. Only strong collision is unacceptable. Then a compliant jointing path planning algorithm based on RRT is designed, combined with some improvements in search efficiency.

A series of planning results show that the efficiency of this method is higher than original RRT under the same conditions. The effectiveness of the method is verified by a series of simulations and experiments on two sets of systems.

There are few reports on the automation technology of helicopter fuselage assembly. This paper analyzes the problem and provides a solution from the perspective of path planning. This method contains a new configuration-space and collision detection method adapted to this problem and could be intuitive for the jointing of other weakly rigid parts.

This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.

The purpose of this paper is that the modular mobile robots reformed the multimachine joint mode to achieve obstacle-crossing, climbing and other multifunctional inspection in unstructured environment under the connection of the cone–hole docking mechanism.

An arc-shaped docking cone head with a posture-maintaining spring and two arc-shaped connecting rods that formed a ring round hole were designed to achieve large tolerance docking. Before active locking, the coordination between structures was used to achieve passive locking, which mitigated the docking impact of modular robots in unstructured environment. Using the locking ring composed of the two arc-shaped connecting rods, open-loop and closed-loop motion characteristics were obtained through the mutual motion of the connecting rod and the sliding block to achieve active locking, which not only ensured high precision docking, but also achieved super docking stability.

The cone–hole docking mechanism had the docking tolerance performance of position deviation of 6mm and pitch deviation of 8° to achieve docking of six degrees of freedom (6-DOF), which had a load capacity of 230 N to achieve super docking stability. Under the connection of the cone–hole docking mechanism, the modular mobile robots reformed the multimachine joint mode to achieve obstacle-crossing, climbing and other multifunctional inspection in unstructured environment.

Based on mechanical analysis of universal models, a cone–hole docking mechanism combining active and passive functions, six-dimensional constraints could be implemented, was proposed in this paper. The characteristics of the posture-maintaining spring in the cone docking head and the compression spring at the two ends of two arc-shaped connecting rods were used to achieve docking with large tolerance. Passive locking and active locking modules were designed, mitigating impact load and the locking did not require power to maintain, which not only ensured high precision docking, but also achieved super docking stability.

This paper examines the circumstantial state of mediated work to develop a conceptual framework exemplifying the determinants of voice of workers in triangular employment relationships. These workers are in work context involving two or more firms – agency/platform and clients/client firms.

Paralleling employee voice research in the triangular employment relationship context, the authors theorised the influencing forces at four levels to propose 12 distinct antecedents of triangular workers' voice. External level (2) – legal employer ambiguity and legal regulation and protection; employment context level (3) – availability and presence, assignment duration and autonomy; firm level (3) – institutional complexity, cost and control and governance structure conflicts; individual level (4) – perceived relative equity, voice skill, self-identity and transition opportunity.

The triangular workers' voice determinants framework provides a comprehensive outlook on how the external, employment context, firm and individual forces influence voice of workers in triangular employment relationships.

Emanating from the framework are propositions that can be empirically tested for validation. Hence, as with conceptual papers, this paper is limited by non-empirical testing.

Managers of workers in these employment relationships should be cognizant of the different levels of forces that can influence their voice.

This paper contributes to the employee voice literature by presenting a four-level framework that demonstrate a holistic view of how triangular workers' voice is influenced.

This chapter will introduce the concept of the gig economy. It begins with a brief discussion of technological changes and their impact on the workforce and labour market, demonstrating how the trend shifts towards the gig economy. It then examines the trends that are influencing this transformation and discusses various perspectives and the attractiveness of the gig economy for workers and businesses. This chapter will also discuss the gig economy, platform economy, digital platform, and gig worker categories. It concludes with a brief discussion of some of the opportunities, issues, and challenges associated with the gig economy.

The unique employment status of gig workers as independent contractors and their impact on consumers provide an important opportunity for the current research to understand gig workers' perceptions of their employment and how that affects job performance outcomes. These gig workers serve as the frontline service providers for platforms like Airbnb hosts, Lyft drivers and Wag walkers performing customer-facing services. However, their status as gig workers, not traditional employees, presents challenges to platforms. The purpose of this research is to gain insights into the profiles of gig workers, examine the challenges platforms have in retaining high-performing workers and provide a research agenda on this important group of frontline service providers.

Incorporating variables deemed important in examining self-determination theory, a large-scale data collection via an online survey was administered, yielding 447 completed surveys. A two-step cluster analysis procedure was conducted to categorize sample respondents into four distinct groups.

Four groups emerged from the cluster analysis, labeled “Ambivalent Outsider,” “Competent Cog,” “Independent Insider” and “Committed Comrade.” The results suggest that there are significant differences across all variables and groups based on gig worker responses and self-reported customer satisfaction scores. The gig worker profiles developed are then utilized to formulate research propositions that are the basis for the research agenda presented.

The goal of many collaborative consumption platforms may be to hire Independent Insiders or Committed Comrades; however, that is difficult to attain with every hire. Thus, the segmentation results provide insights for companies seeking to hire, retain, and successfully motivate their workforce.

Given the freedom and flexibility afforded to gig workers, and the importance they have on the service experience for customers, understanding their own perceptions of employment and performance is critical to ensuring a positive experience for all parties. Research on collaborative consumption has largely focused on consumers or the management of freelance workers with only tangential applicability to gig work. This paper offers a comprehensive research agenda for gig worker management based on the typology of gig workers created.

Many believe that any social media harms kids because of frequent use. This study aims to examine these assumptions. It proposes and tests a model that considers two alternative pathways – one negative and one positive – through which social media affects teens’ self-reported subjective well-being.

This research used Preacher and Hayes process modeling to conduct path analysis on data collected on 585 teenagers from across the USA.

Results showed that along a negative pathway, frequent social media use leads to greater risky social media engagement that ultimately diminishes adolescent’s sense of well-being. Also, and perhaps simultaneously, frequent social media use leads to socially-connected social media use that enhances adolescent’s sense of well-being.

The research recommends ways parents, policymakers and platforms can encourage teens to use social media to connect with friends while guiding them away from pathways exposing them to risky behaviors.

Findings show more social media use is not necessarily harmful, but more of some types is bad, while more of others is good.