A Novel H-Shaped Soft Magnetic Microrobot for Automatic Manipulation in Dynamic Environments

Untethered magnetically actuated soft microrobots are promising in micromanipulation applications. Autonomous navigation and micromanipulation in dynamic environments are challenging because uncertain dynamic obstacles lead to increased planning time and reduced real-time performance. Here, we developed a novel H-shape soft magnetic microrobot with finger behaviors, including gripping and releasing. Without additional stimuli (e.g., light, temperature, etc.), the finger behaviors and movements of the microrobot can be controlled simultaneously by adjusting the strength and direction of the magnetic fields. We proposed a sliding-window-based local dynamic path planning method in dynamic environments to address the drawbacks of inefficiency and the high computational cost of global search. An enhanced optimized rapidly-exploring random tree algorithm is developed for planning avoidance paths at a safe distance from the boundary of obstacles. In order to automatically manipulate multiple objects, the manipulation process is quantitatively divided into several subtasks, and a finite state machine (FSM) based task planner is proposed to control the switching between subtasks. Experiments demonstrate the autonomous obstacle avoidance and navigation of the microrobot in dynamic environments with obstacles moving 2.5 times faster than the robot. Eight spherical objects of 2 mm diameter were automatically transported to the corresponding target position with an average error of 0.29 mm and an average transport time of 17.25 seconds. In the future, this work promises to enable automated cell sorting by microrobots. Note to Practitioners—This article was motivated by the recent interest in utilizing the small-scale microrobots to perform micromanipulation tasks. For automated manipulation of objects, effective Untethered actuation, manipulation behavior control, and navigation are required. Besides, obstacle avoidance and dynamic obstacles in the environment need to be considered. The strategy proposed here is developed for automated multi-object manipulation via a novel soft magnetic microrobot. The developed task planner quantitatively divides the operation process into several subtasks and controls the switching between them. The dynamic path planning algorithm is used to efficiently search for collision avoidance paths in dynamic obstacle environments. The motion-behavior coordination controller is used to control the robot to perform manipulation subtasks. Experimental results have validated the proposed strategy in actuation, navigation, and multiple cargoes manipulation in dynamic obstacle environments.