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The motion planning is a critical component of autonomous navigation, requiring the vehicle to reach a target location safely. Traditional navigation approaches for four-wheel differential drive automated guided vehicles...

Background and Purpose: Deep learning segmentation (DLS) and planning (DLP) models in radiotherapy treatment planning increase consistency and reduce planning time. However, many DL segmentations and plans are manually a...

This study addresses the under-explored dynamic characteristics of unmanned ships in trajectory planning by constructing a constraint space in the navigation state-phase plane. First, we employ a path-velocity decoupling...

In response to the limitations of traditional planning methods for Autonomous Surface Vehicles (ASVs), which heavily rely on predefined map representations and neglect kinematic feasibility, this paper proposes a novel k...

Reirradiation is increasingly used for recurrent and new primary cancers, but dedicated planning tools are limited. We integrated deformable image registration and radiobiologically consistent dose accumulation into plan...

Background: High tibial osteotomy (HTO) surgical accuracy may be improved by using CT-based pre-operative planning and patient-specific cutting guides (PSCGs). This randomized exploratory study aimed to assess the feasib...

Objective: To develop an artificial intelligence (AI) driven plan tradeoff decision making assistant for radiation oncologists. Methods: A user interface (UI) was developed to integrate the assistant with the treatment p...

Despite the growing number of interventions aimed at reducing household food waste (HFW), many remain overly generalised and fail to adequately account for the heterogeneous routines, motivations, and disposal contexts t...