For soft grippers to be applied in atypical industrial environments, they must conform to an object’s exterior shape and momentarily change their stiffness. However, many of the existing grippers have limitations with respect to these functions: they grasp an object with only a single curvature and a fixed stiffness. Consequently, those constraints limit the stability of grasping and the applications. This paper introduces a new multicurvature, variable-stiffness soft gripper. Inspired by the human phalanx and combining the phalanx structure and particle jamming, this work guarantees the required grasping functions. Unlike the existing soft pneumatic grippers with one curvature and one stiffness, this work tries to divide the pressurized actuating region into three parts to generate multiple curvatures for a gripper finger, enabling the gripper to increase its degrees of freedom. Furthermore, to prevent stiffness loss at an unpressurized segment, this work combines divided actuation and the variable-stiffness capability, which guarantee successful grasping actions. In summary, this gripper generates multiple grasping curvatures with the proper stiffness, enhancing its dexterity. This work introduces the new soft gripper’s design, analytical modeling, and fabrication method and verifies the analytic model by comparing it with FEM simulations and experimental results.

This article presents an optimal admittance control method for safe and smooth human–robot collaboration, where velocity and jerk are constrained to maintain safety without compromising manipulability. While limiting velocity is essential for safety in physical human–robot interaction (pHRI), it often causes abrupt jerk changes that degrade performance. Resolving this requires a smooth deceleration profile and accurate prediction of the final velocity at the end of deceleration. To address this challenge, an optimal control approach is developed to generate velocity profiles satisfying predefined limits on velocity and jerk. In addition, the overall system's passivity is achieved through an adaptive PD controller that regulates the null-space dynamics of redundant manipulators. This method achieves benefits similar to energy tank approaches while ensuring more reliable passivity without explicit energy management. The proposed method is validated through ISO/TS 9241-411 Fitts' law experiments, demonstrating that this safety-enhancing method maintains operational performance comparable to that of unconstrained controllers. Additional experiments validate the controller's real-time responsiveness, showing its ability to adapt immediately to real-time changes in speed limits and achieve rapid, stable trajectory adjustments. These results highlight the method's applicability to pHRI environments requiring stringent safety and consistent operational performance.