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Although researchers have demonstrated a significant interest in motivation factors of knowledge collaboration, previous studies have seldom explored the dynamic interrelations in virtual communities of practice (VCoPs) over time that involve the iteratively melding of knowledge collaboration motivations and behaviours. Therefore, this study aims to unveil the interactive dynamics amongst motivation factors of knowledge collaboration in VCoPs from a perspective of system dynamics (SD).

According to the SD method proposed by Forrester, this paper develops an SD model of motivation factors of knowledge collaboration in VCoP by identifying interactions of motivation factors based on behavioural theories, validating the proposed model by structural tests and behaviour tests involving historical data from 939 Wikipedians and analysing the impacts of policy regulations on knowledge collaboration behaviours in Wikipedia.

In accordance with current literature, this study categorises intrinsic, extrinsic and community motivation factors of knowledge collaborations in VCoPs. According to the SD method, this study develops and validates an SD model to reveal interesting non-linear dynamics of these motivation factors which are neglected by prior studies. This study also conducts dynamic what-if analyses to suggest policy regulations to promote knowledge collaborations in the context of Wikipedia.

Different from prior empirical studies which normally take on a snapshot of motivation factors, this study discloses a dynamic picture of their interrelations by unfolding their behaviour patterns over time. The main contribution of this paper is to develop and validate an SD model of motivation factors of knowledge collaboration in VCoP and to reveal and elaborate their dynamics for policy regulations in VCoPs based on simulation results.

In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.

This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.

This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.

To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.

Nowadays, the global agricultural system is highly dependent on the widespread use of synthetic pesticides to control diseases, weeds and insects. The unmanned aerial vehicle (UAV) is deployed as a major part of integrated pest management in a precision agriculture system for accurately and cost-effectively distributing pesticides to resist crop diseases and insect pests.

With multimodal sensor fusion applying adaptive cubature Kalman filter, the position and velocity are enhanced for the correction and accuracy. A dynamic movement primitive is combined with the Gaussian mixture model to obtain numerous trajectories through the teaching of a demonstration. Further, to enhance the trajectory tracking accuracy under an uncertain environment of the spraying, a novel model reference adaptive sliding mode control approach is proposed for motion control.

Experimental studies have been carried out to test the ability of the proposed interface for the pesticides in the crop fields. The effectiveness of the proposed interface has been demonstrated by the experimental results.

To solve the path planning problem of a complex unstructured environment, a human-robot skills transfer interface is introduced for the UAV that is instructed to follow a trajectory demonstrated by a human teacher.

Excellent obstacle surmounting performance is essential for the robotic vehicles in uneven terrain. However, existing robotic vehicles depend on complex mechanisms or control algorithms to surmount an obstacle. Therefore, this paper aims to propose a new simple configuration of an all-terrain robotic vehicle with eight wheels including four-swing arms.

This vehicle is driven by distributed hydraulic motors which provide high mobility. It possesses the ability to change the posture by means of cooperation of the four-swing arms. This ensures that the vehicle can adapt to complex terrain. In this paper, the bionic mechanism, control design and steering method of the vehicle are introduced. Then, the kinematic model of the center of gravity is studied. Afterward, the obstacle surmounting performance based on a static model is analyzed. Finally, the simulation based on ADAMS and the prototype experiment is carried out.

The experiment results demonstrate that the robotic vehicle can surmount an obstacle 2.29 times the height of the wheel radius, which verifies the feasibility of this new configuration. Therefore, this vehicle has excellent uneven terrain adaptability.

This paper proposes a new configuration of an all-terrain robotic vehicle with four-swing arms. With simple mechanism and control algorithms, the vehicle has a high efficiency of surmounting an obstacle. It can surmount a vertical obstacle 2.29 times the height of the wheel radius.