The soft robotics field investigates biological bodies' movements to develop soft actuation with similar behavior seen in nature. The skeletal muscles' movements are vastly mimicked in soft actuators; however, the contractions of smooth muscles are overlooked in soft robotics. Smooth muscles provide peristaltic contractions to the digestive system, such as the stomach, and their design challenges the limits of soft robot development that simulates digestive organs. We present a novel, bellows-driven soft pneumatic actuator (SPA) with a self-sensing capability that generates linear displacement to simulate a smooth muscle segment in a stomach. This SPA is proposed as a solution for applications such as stomach simulators. The SPA concept, design, fabrication, creep model, and experimental validation are presented in this paper. A lumped viscoelastic model presents the actuator's modeling to predict the SPA's displacement from a known applied pressure. The model is successfully validated, which resulted in a maximum displacement of 20.0 mm with a displacement error of 3%. A sensory system embedded in the SPA measures the displacement, and it is found that a force of 0 to 8.0 N is produced. A polynomial equation calibrates the sensor readings, with a displacement error of 5%. The results show the SPA's capability as a linear soft actuator that can generate a deformation like a smooth muscle segment. To simulate a circular contraction from a stomach with the SPA, we install multi-SPAs in a ring frame that performs contractions. Although the proposed SPA is specifically designed to mimic the smooth muscle, the ring actuator's contractions can be used for other applications such as gripping soft objects.

In this article, the development of a control framework for a soft robotic table is presented. The framework aims to enable the soft table to effectively manipulate an object to track a reference trajectory. The table system has been modeled using empirical methods via experiments and finite-element analysis simulations. A closed-loop trajectory tracking system, including a trajectory controller, a vision feedback, and a reference trajectory, has been designed. An algorithm to allocate actuation has been developed to implement the tracking system into the existing soft table system. Finally, simulations and experiments using different tracking controllers of an object tracking a circular trajectory have been conducted to validate the proposed trajectory tracking system. The experimental result shows that the tracking error remains within 3.4 mm for the $X$ -axis and 4 mm for the $Y$ -axis. The error in orientation remains within 12.8 $^\circ$ . All the errors are bounded in the acceptable margin, which proves the effectiveness of the proposed trajectory tracking control method.

This paper presents the mechatronics design, modelling and characterization of a soft robotic table inspired by caterpillar locomotion. The table is capable of manipulating objects on the XY horizontal plane through surface deformations. The full realization of the table system including its actuation system, pneumatic system, electrical system and user interface is discussed. The analytical modelling of these systems is explained. A design technique for the table is presented where its performance can be tuned by modifying its parameters via finite element analysis. The characteristics of the soft table are evaluated in terms of its hardware capabilities and object manipulation capabilities. These are important for the development of the table's control system. The key functional and operational parameters of the table such as the maximum object load, operational speed and power consumptions are discussed. Experiments are conducted on three distinct objects to analyse the performance of object movement. Object transportability is analysed based on the object's shape, size and weight. The unique features of the table including the intrinsic soft handling of objects and simultaneous multiple object manipulation are validated. The soft table in action of various object manipulations can be viewed in the video supplied.

This paper presents a control strategy to carry out multi-object manipulation on a novel s oft r o botic ta ble (SoTa), which is a new form of the planar distributed manipulator. Manipulating multiple delicate objects simultaneously is an attractive feature of SoTa. The challenge here is to coordinate multiple objects in a confined planar space while avoiding interference with each other. The SoTa system adopts a manipulation strategy that includes a planning and a tracking stage for the purpose of sorting objects. The planning stage consists of two phases: 1) discrete path planning to find a path for each object on a grid map with respect to time; 2) trajectory generation to optimize and produce workable trajectories for SoTa. In the discrete path planning phase, a hierarchical searching method based on the time-varying potential field is proposed. Constraints of the SoTa system are modelled and incorporated into the path searching process. In the trajectory generation phase, a piecewise B-spline method is adopted to generate trajectories based on previously found discrete paths. Next, in the tracking stage, the objects are led to their goals along the trajectories ensuring safety and SoTa's capability. The performances of the proposed algorithm were simulated, analyzed, and compared with the conflict-based search (CBS) method which is optimal for multi-agent path finding. A multi-object manipulation experiment of three objects on a $4\times 4$ grid was conducted on the SoTa. The results demonstrated the effectiveness of the proposed control strategy in executing multi-object manipulations for sorting tasks on the SoTa.

In-vitro gastric simulators are soft robotic systems that reproduce the change of the food or drug by emulating the stomach's motility functions. The control of gastric simulators traditionally lies in tuning the actuators via open-loop approaches. However, the lack of precise position control, external disturbances, sensitivity to model uncertainties, and continues retuning are solid motivations for employing closed-loop methods to control gastric simulators. A bellows-driven viscoelastic soft ring-shaped pneumatic actuator (RiSPA), including five spring-like bellows, was developed for stomach simulators’ primary actuation system. This article studies the implementation of closed-loop methods equipped with the online feedback system on the RiSPA for the first time. All technical aspects for implementing the closed-loop control and the sensor-actuator integration are discussed in detail. A model-based closed-loop method has been implemented and compared with a classic model-free method to show the closed-loop system's ability to reject model uncertainties. The experimental results in both the tracking trajectory and the regulation performances are thoroughly compared to the open-loop approach, where the superiority of closed-loop techniques is demonstrated. A mechanical setup is designed to show the ability of the closed-loop approach in dealing with the disturbances and external loads as well.

This article presents the design, development, and validation of a closed-loop control system for a soft robotic table. The soft table can provide independent manipulation to multiple objects simultaneously, which is an advantage over traditional devices such as robotic arms and belt conveyor systems. The table also provides intrinsic soft handling for delicate objects. In order to execute automation tasks, a vision feedback system and an operation controller are developed and incorporated into the existing table prototype to form a closed-loop control. The vision feedback system implements image processing techniques to identify the object location from captured images. The operation controller is integrated from three sets of algorithms, including movement planning, actuator selection, and actuation planning. Two sets of experiments were conducted to validate the closed-loop system and the capability of the soft table. The first set validated the manipulation task of transporting an object to a desired location with autonomous planning and execution. The second set validated the table's ability to manipulate multiple objects simultaneously and independently. Videos of both experiments have been supplied.