Geometry-based pneumatic actuators for soft robotics

Soft pneumatic actuators are widely used in soft robotics because they can produce large motions while remaining compliant enough to interact safely with objects, environments, and the human body. However, their performance is not solely determined by pressure. Instead, the response depends on the way the actuator is built, including the shape of its chambers, the placement of reinforcements, the use of folds, material stiffness, and the constraints that guide its deformation. As the literature has expanded, it has become more difficult to determine which mechanism is most suitable for a given application and which reported results can be compared across studies. This review examines soft pneumatic actuators according to the design strategies used to generate four motion classes: linear, bending, twisting, and omnidirectional actuation. For each class, it analyzes the structural features that define the deformation path, including braid angle, fold geometry, fiber orientation, chamber arrangement, structural asymmetry, and internal constraint layers. It then discusses how the design choice affect motion output, force generation, air demand, repeatability, durability, fabrication difficulty, and robotic integration. The review further identifies key conditions that must be considered when selecting or comparing actuators, including pressure, loading condition, actuator size, pneumatic supply, and hysteresis This approach helps explain why actuators with similar motion outputs may differ substantially in design requirements, pneumatic demand, and practical suitability. It also highlights the design priorities needed for compact, efficient, repeatable, and deployable soft pneumatic systems in wearable, biomedical, and mobile robotic applications.

Soft pneumatic actuators are widely used in soft robotics. However, their actuation modes are typically fixed by internal chamber designs or reinforcements, making post fabrication reconfiguration difficult. This paper presents a reconfigurable fabric-based pneumatic actuator that enables rapid, tool free, and reusable switching among multiple actuation modes by attaching constraint fabric modules to a buttoned textile sleeve. By rearranging low-stretch constraint parts on a single actuator body, the proposed system realizes four actuation modes isotropic expansion, contraction, bending, and twisting without redesigning or disassembling the actuator.We further introduce an attachable capacitive fabric-based tactile sensor module that can be mounted at arbitrary locations on the actuator surface for task dependent contact sensing. Experiments demonstrated an elongation ratio of 1.2, a maximum bending angle of approximately 60 degrees, and a twisting angle of approximately 90 degrees at 24 kPa, while achieving blocking forces exceeding 10 N across all modes. The tactile sensor exhibited a monotonic, force-dependent increase in capacitance with low hysteresis (approximately 12%) and stable cyclic responses under preload. Finally, we constructed soft robotic arms composed of multiple actuators and demonstrated in situ motion reconfiguration for grasping by changing the attached constraint patterns. These results indicate that the proposed modular constraint and sensing framework improves the functional adaptability of fabric-based soft robots while preserving a simple, robust actuator structure.

Modern robots embody power and precision control. Yet, as robots undertake tasks that apply forces on humans, this power brings risk of injury. Soft robotic actuators use deformation to produce smooth, continuous motions and conform to delicate objects while imparting forces capable of safely pushing humans. This thesis presents strategies for the design, modeling, and strain-based control of human-safe elastomeric soft pneumatic actuators (SPA) for force generation, focusing on embodied mechanical response to simple pressure inputs. We investigate electroadhesive (EA) strain limiters for variable shape generation, rapid force application, and targeted inflation trajectories. We attach EA clutches to a concentrically strain-limited elastomeric membrane to alter the inflation trajectory and rapidly reorient the inflated shape. We expand the capabilities of EA for soft robots by encasing them in elastomeric sheaths and varying their activation in real time, demonstrating applications in variable trajectory inflation under identical pressure sweeps. We then address the problem of trajectory control in the presence of external forces by modeling the pressure-trajectory relationship for a concentrically strain-limited class of silicone actuators. We validate theoretical models based on material properties and energy minimization using active learning and automated testing. We apply our ensemble of neural networks for inverse membrane design, specifying quasi-static mass lift trajectories from a simple pressure sweep. Finally, we demonstrate the power of multiple pressure-linked actuators in a proof-of-concept mannequin leg lift.