Multi-area collision-free path planning and efficient task scheduling optimization for autonomous agricultural robots.

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.

One-step preparation of hybrid materials of polyacrylamide networks and gold nanoparticles.

Hybrid materials of polyacrylamide networks and gold nanoparticles were prepared by directly heating an aqueous solution containing HAuCl(4), acrylamide, N,N'-methylenebis-acrylamide, and sodium sulfite (Na(2)SO(3)). Acrylamide, N,N'-methylenebis-acrylamide, and Na(2)SO(3) were used as monomers, crosslinking agent, and initiator, respectively. In the process of polyacrylamide network synthesis, HAuCl(4) was reduced by acrylamide and Na(2)SO(3) into gold nanoparticles and adsorbed on the produced polyacrylamide networks. Transmission electron microscopy proved that the size of gold nanoparticles was in the range of 3-10 nm. Atomic force microscopy showed that the gold nanoparticles homogeneously dispersed into the polyacrylamide networks matrix. The hybrid materials as absorbents may be useful in healthcare, communication technology, building industry, chromatography, water purification, and agriculture.