In this work, a helical ionic polymer metal composite (IPMC) was fabricated by thermal treatment in a mold with helix grooves. The axial actuation behaviors of the helical IPMC actuator were observed, and the electromechanical and electrochemical characteristics were evaluated. The experimental results showed that as the voltage increased and the frequency decreased, the axial displacement, axial force, and electric current of the actuator all increased. Compared with square wave and sinusoidal signals, the actuator exhibited the most satisfactory motion under the direct current (DC) signal. For the electrochemical test, as the scanning rate decreased, the gravimetric specific capacitance increased. Within a suitable voltage range, the actuator was chemically stable. In addition, we coupled the Electrostatics module, Transport of Diluted Species module, and Solid Mechanics module in COMSOL Multiphysics software to model and analyze the helical IPMC actuator. The simulation data obtained were in good agreement with the experimental data. Finally, by using three helical IPMC actuators as driving components, an innovative three-degree-of-freedom (3-DOF) micro-parallel platform was designed, and it could realize a complex coupling movement of pitch, roll, and yaw under the action of an electric field. This platform is expected to be used in micro-assembly, flexible robots, and other fields.

Multi-vehicle tracking is used in advanced driver assistance systems to track obstacles, which is fundamental for high-level tasks. It requires real-time performance while dealing with object illumination variations and deformations. To this end, we propose a novel multi-vehicle tracking algorithm based on a monocular camera in driver view. It follows the tracking-by-detection paradigm and integrates detection and appearance descriptors into a single network. The one-stage detection approach consists of a backbone, a modified BiFPN as a neck layer, and three prediction heads. The data association consists of a two-step matching strategy together with a Kalman filter. Experimental results demonstrate that the proposed approach outperforms state-of-the-art algorithms. It is also able to solve the tracking problem in driving scenarios while maintaining 16 FPS on the test dataset.