Every apple destined for the fresh market is picked by the human hand. Despite extensive research over the past four decades, there are no mechanical apple harvesters for the fresh market commercially available, which is a significant concern because of increasing uncertainty about the availability of manual labor and rising production costs. The highly unstructured orchard environment has been a major challenge to the development of commercially viable robotic harvesting systems. This paper reports the design and field evaluation of a robotic apple harvester. The approach adopted was to use a low-cost system to assess required sensing, planning, and manipulation functionality in a modern orchard system with a planar canopy. The system was tested in a commercial apple orchard in Washington State. Workspace modifications and performance criteria are thoroughly defined and reported to help evaluate the approach and guide future enhancements. The machine vision system was accurate and had an average localization time of 1.5 s per fruit. The seven degree of freedom harvesting system successfully picked 127 of the 150 fruit attempted for an overall success rate of 84% with an average picking time of 6.0 s per fruit. Future work will include integration of additional sensing and obstacle detection for improved system robustness.

Soft robotics as a field of study incorporates different mechanisms, control schemes, as well as multifunctional materials to realize robots able to perform tasks inaccessible to traditional rigid robots. Conventional methods for controlling soft robots include pneumatic or hydraulic pressure sources, and some more recent methods involve temperature and voltage control to enact shape change. Magnetism was more recently introduced as a building block for soft robotic design and control, with recent publications incorporating magnetorheological fluids and magnetic particles in elastomers, to realize some of the same objectives present in more traditional soft robotics research. This review attempts to organize and emphasize the existing work with magnetism and soft robotics, specifically studies on magnetic elastomers, while highlighting potential avenues for further research enabled by these advances.

No abstract

This paper reviews recent developments in energy harvesting technologies for structural health monitoring applications. Many industries have a great deal of interest in obtaining technology that can be used to monitor the health of machinery and structures. In particular, the need for autonomous monitoring of structures has been ever-increasing in recent years. Autonomous SHM systems typically include embedded sensors, data acquisition, wireless communication, and energy harvesting systems. Among all of these components, this paper focuses on the energy harvesting technologies. Since low-power sensors and wireless communications are used in newer SHM systems, a number of researchers have recently investigated techniques to extract energy from the local environment to power these stand-alone systems. Ambient energy sources include vibration, thermal gradients, solar, wind, pressure, etc. If the structure has a rich enough loading, then it may be possible to extract the needed power directly from the structure itself. Harvesting energy using piezoelectric materials by converting applied stress to electricity is most common. Other methods to harvest energy such as electromagnetic, magnetostrictive, or thermoelectric generator are also reviewed. Lastly, an energy harvester with frequency tuning capability is demonstrated.

No abstract