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Traditional robot arm trajectory planning methods have problems such as insufficient generalization performance and low adaptability. This paper aims to propose a method to plan the robot arm’s trajectory using the trajectory learning and generalization characteristics of dynamic motion primitives (DMPs).

This study aligns multiple demonstration motion primitives using dynamic time warping; use the Gaussian mixture model and Gaussian mixture regression methods to obtain the ideal primitive trajectory actions. By establishing a system model that improves DMPs, the parameters of the nonlinear function are learned based on the ideal primitive trajectory actions of the robotic arm, and the robotic arm motion trajectory is reproduced and generalized.

Experiments have proven that the robot arm motion trajectory learned by the method proposed in this article can not only learn to generalize and demonstrate the movement trend of the primitive trajectory, but also can better generate ideal motion trajectories and avoid obstacles when there are obstacles. The maximum Euclidean distance between the generated trajectory and the demonstration primitive trajectory is reduced by 29.9%, and the average Euclidean distance is reduced by 54.2%. This illustrates the feasibility of this method for robot arm trajectory planning.

It provides a new method for the trajectory planning of robotic arms in unstructured environments while improving the adaptability and generalization performance of robotic arms in trajectory planning.

There is a growing recognition of the urgency to enhance health outcomes for children and young people residing in out-of-home care (OOHC). Research underscores the need to establish effective pathways to quality health care for children and young people who have been exposed to trauma. Child protection (CP) practitioners should play a vital role in proactively improving health outcomes and navigating the intricacies of healthcare systems. Their involvement in initiating and collaborating on healthcare interventions is pivotal for the well-being of these vulnerable children and young people. However, challenges associated with poor health literacy and the complexities of healthcare systems hinder collaborative service delivery in the Australian context. This review explores how CP practitioners support the health care of children and young people in their care.

A scoping review followed Arksey and O’Malley’s framework, employing a narrative synthesis to assess the selected studies.

Health outcomes for children and young people in OOHC remain under-researched and potentially under-resourced within the realm of CP practice. There is room for enhanced practices and system integration in CP service delivery to better address health needs and prevent further health and well-being disparities.

Through this scoping review and involving industry experts in the discussion of findings, this study contributes valuable insights to the existing knowledge base regarding the active participation of CP practitioners in addressing the healthcare needs of vulnerable children.