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Good path planning technology of mobile robot can not only save a lot of time, but also reduce the wear and capital investment of mobile robot. Several methodologies have been proposed and reported in the literature for the path planning of mobile robot. Although these methodologies do not guarantee an optimal solution, they have been successfully applied in their works. The purpose of this paper is to review the modeling, optimization criteria and solution algorithms for the path planning of mobile robot. The survey shows GA (genetic algorithm), PSO (particle swarm optimization algorithm), APF (artificial potential field), and ACO (ant colony optimization algorithm) are the most used approaches to solve the path planning of mobile robot. Finally, future research is discussed which could provide reference for the path planning of mobile robot.

A triple-shape memory polyurethane (TSMPU) with poly(ε-caprolactone) -diols (PCL-diols) as the soft segments and diphenyl methane diisocyanate (MDI), N,N-bis (2-hydroxyethyl) cinnamamide (BHECA) as the hard segments was synthesized via simple photo-crosslinking of cinnamon groups irradiated under λ > 280 nm ultraviolet (UV) light. Fourier transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance ( 1 H-NMR) and ultraviolet-visible absorption spectrum (UV−vis) confirmed the chemical structure of the material. Differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) results demonstrated that the photocrosslinked polymer possessed two transition temperatures, one is due to the melting point of the soft segment PCL-diols, and the other is due to the glass transition temperature. All these contributed to the cross-linked structure of the hard segments and resulted in an excellent triple-shape memory effect. Alamar blue assay showed that the material has good non-cytotoxicity and can be potentially used in biomaterial devices.

Shape-switchable micrometer-sized particles have the ability to reversibly switch their shapes between 43 and 0 °C via a two-way shape memory effect.

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The development of food-grade (nano)particles as a delivery system for poorly water soluble bioactives has recently attracted increasing attention. This work is an attempt to fabricate food protein-based nanoparticles as delivery systems for improving the water dispersion and bioaccessibility of phytosterols (PS) by an emulsification-evaporation method. The fabricated PS nanoparticles were characterized in terms of particle size, encapsulation efficiency (EE%) and loading amount (LA), and ξ-potential. Among all the test proteins, including soy protein isolate (SPI), whey protein concentrate (WPC) and sodium caseinate (SC), SC was confirmed to be the most suitable protein for the PS nano-formulation. Besides the type of protein, the particle size, EE% and LA of PS in the nanoparticles varied with the applied protein concentration in the aqueous phase and organic volume fraction. The freeze-dried PS nanoparticles with SC exhibited good water re-dispersion behavior and low crystallinity of PS. The LA of PS in the nanoparticles decreased upon storage, especially at high temperatures (e.g., >25 °C). The PS in the fabricated nanoparticles exhibited much better bioaccessibility than free PS. The findings would be of relevance for the fabrication of food-grade colloidal phytosterols, with great potential to be applied in functional food formulations.

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