Collision-free path planning and task scheduling optimization in multi-region operations of autonomous agricultural robots present a complex coupled problem. In addition to considering task access sequences and collision-free path planning, multiple factors such as task priorities, terrain complexity of farmland, and robot energy consumption must be comprehensively addressed. This study aims to explore a hierarchical decoupling approach to tackle the challenges of multi-region path planning. Firstly, we conduct path planning based on the A* algorithm to traverse paths for all tasks and obtain multi-region connected paths. Throughout this process, factors such as path length, turning points, and corner angles are thoroughly considered, and a cost matrix is constructed for subsequent optimization processes. Secondly, we reformulate the multi-region path planning problem into a discrete optimization problem and employ genetic algorithms to optimize the task sequence, thus identifying the optimal task execution order under energy constraints. We finally validate the feasibility of the multi-task planning algorithm proposed by conducting experiments in an open environment, a narrow environment and a large-scale environment. Experimental results demonstrate the method's capability to find feasible collision-free and cost-optimal task access paths in diverse and complex multi-region planning scenarios.

The objective of image fusion is to integrate complementary features from source images to better cater to the needs of human and machine vision. However, existing image fusion algorithms predominantly focus on enhancing the visual appeal of the fused image for human perception, often neglecting their impact on subsequent high-level visual tasks, particularly the processing of semantic information. Moreover, these fusion methods that incorporate downstream tasks tend to be overly complex and computationally intensive, which is not conducive to practical applications. To address these issues, a lightweight infrared and visible light image fusion method known as SIFusion, which is based on semantic injection, is proposed in this paper. This method employs a semantic-aware branch to extract semantic feature information, and then integrates these features into the fused features through a Semantic Injection Module (SIM) to meet the semantic requirements of high-level visual tasks. Furthermore, to simplify the complexity of the fusion network, this method introduces an Edge Convolution Module (ECB) based on structural reparameterization technology to enhance the representational capacity of the encoder and decoder. Extensive experimental comparisons demonstrate that the proposed method performs excellently in terms of visual appeal and advanced semantics, providing satisfactory fusion results for subsequent high-level visual tasks even in challenging scenarios.

To address the issues of significant brittleness and susceptibility to catastrophic failure in traditional gangue-based cemented backfill, this study designed and prepared steel fiber and fly ash reinforced gangue backfill (FGB). Through macroscopic mechanical testing and Discrete Element Method (DEM) numerical simulation, the synergistic effects of steel fiber (VSF=0.0~2.0%) and fly ash (ωFA=5~15%) content on the mechanical properties, energy evolution, and failure modes of the FGB were systematically investigated. The results indicate that steel fibers and fly ash significantly improve the mechanical properties and failure modes of the backfill. The steel fiber content exhibits a linear positive correlation with the strength of the backfill, while the fly ash content shows a negative correlation with strength. The incorporation of fly ash enhances energy dissipation, and steel fibers effectively regulate the distribution ratio between elastic energy and dissipated energy. The addition of steel fibers and fly ash caused the crack type in the backfill to shift from a predominantly S-type to a composite S, T, and ST failure mode, and the failure mechanism transformed from a brittle mode controlled by a single dominant crack to a ductile mode characterized by multi-crack propagation. The fibers restructured the three-dimensional stress chain network, altering stress transfer pathways, increasing horizontal contact forces and the density of stress chains, and enabling the gradual transfer of stress from localized failure zones to the entire structure. This study provides a reference for the development of high-toughness, high-performance mine backfill materials.