There are many instances of helical mechanisms that are used to efficiently grasp different objects with various shapes and sizes in nature. Inspired by the helical grasping in the nature, we proposed a helical bistable soft gripper with high load capacity and energy saving. An off-the-shelf bistable steel shell (BSS) as the stiff element was inserted into a 3D printing soft helical exoskeleton to achieve coiling around and holding the objects without energy consumption. Two air pouches were designed as the actuator to control the transition between the two stable states. To facilitate gripper design, a simplified model of the gripper was conducted, and the geometric parameters of the gripper are listed in a table for reference. The transition pressures between the two stable states were experimentally characterized. Moreover, we conduct experiments to demonstrate the capability of the gripper in two working modes. The gripper exhibits coiling diameters ranging between 40 mm and 60 mm and is successfully attached to various slender objects of different geometries with a maximum holding force of 92.67 N (up to 135.1 times of its mass) in hanging mode. Finally, the gripper was integrated into a robot arm and successfully grasped different objects, and the maximum grasping weight is 221.6 g in the grasping mode.

Lake shoreline detection plays an important role in hydrological structure analysis and urban ecology governance but is a challenging task in synthetic aperture radar (SAR) image interpretation. Due to the complex shoreline environment, the preservation of weak boundaries and fitting of global information in large-scale SAR images deserve further research. Thus, this letter proposes a novel coarse-to-fine lake shoreline detection approach for SAR images based on modified region-scalable fitting (RSF) model combined with edge energy and global energy. In this approach, SAR images are despeckled by the block-matching 3-D (BM3D) filter. Then a novel energy term based on Laplacian of Gaussian (LoG) operator and ratio of exponentially weighted averages (ROEWA) operator is constructed to accurately locate the boundary and reduce false boundary. Additionally, the global energy term is adopted to fit the global information well. The experimental results based on real data demonstrate that the proposed approach has a stronger ability to maintain weak edges compared with RSF model, which exhibits better effectiveness and reliability.