This paper presents a soft actuator inspired by origami and a tunable strain limiting layer, which is proposed for reconfigurable soft robotic grasping. Main structure of the actuator is based on Miura origami which generates extension under pressurized air while a limiting layer with tunable length enables the actuator with different motion patterns. By driving the limiting layer through a servo motor, the range of motion and trajectory of the actuator can be pre-programed and the gripper’s grasping range will be affected accordingly. This paper discusses the design, fabrication, analysis and experimental verification of the actuator. Then grasping performance of the gripper under objects of different shapes, sizes, and weights is experimentally evaluated. The reconfigurable soft gripper can be applied as an end-effector to accomplish adaptive grasping tasks with various targets.

Grasping and manipulating various kinds of objects cooperatively is the core skill of a dual-arm robot when deployed as an autonomous agent in a human-centered environment. This requires fully exploiting the robot's versatility and dexterity. In this work, we propose a general framework for dual-arm manipulators that contains two correlative modules. The learning-based dexterity-reachability-aware perception module deals with vision-based bimanual grasping. It employs an end-to-end evaluation network and probabilistic modeling of the robot's reachability to deliver feasible and dexterity-optimum grasp pairs for unseen objects. The optimization-based versatility-oriented control module addresses the online cooperative manipulation control by using a hierarchical quadratic programming formulation. Self-collision avoidance and dual-arm manipulability ellipsoid tracking with high reliability and fidelity are simultaneously achieved based on a learned lightweight distance proxy function and a speed-level tracking technique on Riemannian manifold. Intrinsic system safety is guaranteed, and a novel interface for skill transfer is enabled. A long-horizon rearrangement experiment, a bimanual turnover manipulation, and multiple comparative performance evaluation verify the effectiveness of the proposed framework.

Owing to high compliance, adaptiveness, and easy controllability, soft actuators are widely adopted in soft grippers to grasp irregularly shaped or fragile objects. The specific motions can be preprogrammed into the flexible and constrained structures of the actuator, which provides an inexpensive and convenient method for desired motions. However, most preprogrammed structures cannot change the constraints on the actuator to achieve different kinds of deformations, which limits the motion diversities of actuators. This article proposes a scaffold reinforcement mechanism, where rotatable scaffolds distribute on the surface of the soft structure. The orientation adjustments of the scaffolds can change the deformation constraint of the actuator, which results in different kinds of motions. Based on the scaffold reinforcement mechanism, a scaffold-reinforced actuator is proposed, which can achieve bending motion and complex helical motion in the 3-D space by properly adjusting the orientation of the scaffolds. In addition, both the kinematic and mechanical models are proposed to forecast the behavior of the actuator when driven by cable displacement or tension force. Experimental results verify the validity of the theoretical model, and the actuator can achieve an independent control of bending and helical motion, which can be adopted in applications where both high dexterity and flexibility are required.

Monitoring the state of contact is essential for robotic devices, especially grippers that implement geckoinspired adhesives where intimate contact is crucial for a firm attachment. However, due to the lack of deformable sensors, few have demonstrated tactile sensing for gecko grippers. We present Viko, an adaptive gecko gripper that utilizes vision-based tactile sensors to monitor contact state. The sensor provides high-resolution real-time measurements of contact area and shear force. Moreover, the sensor is adaptive, low-cost, and compact. We integrated gecko-inspired adhesives into the sensor surface without impeding its adaptiveness and performance. Using a robotic arm, we evaluate the performance of the gripper by a series of grasping test. The gripper has a maximum payload of 8N even at a low fingertip pitch angle of 30°. We also showcase the gripper’s ability to adjust fingertip pose for better contact using sensor feedback. Further, everyday object picking is presented as a demonstration of the gripper’s adaptiveness.

Structures with origami design enable objects to transform into various three-dimensional shapes. Traditionally origami structures are designed with zero-thickness flat paper sheets. However, the thickness and intersection of origami facets are non-negligible in most cases, uniquely when integrating origami design with robotic design because of the more efficient force transfer between thick plates compared with zero-thickness paper-sheets. Meanwhile, the single-layer-paper oriented initial design limited the shape transformation potential as multiple layer origami structures could conduct more variety of deformation. In this article, we are proposing a general design method of parallel-motion thick origami structures that could apply in robotic design like a parallel-motion gripper.

The supercoiled polymer (SCP) actuator is a novel artificial muscle, which is manufactured by twisting and coiling polymer fibers. This new artificial muscle is soft, low-cost and shows good linearity. Being utilized as an actuator, the artificial muscle could generate significant mechanical power in a muscle-like form upon electrical activation by Joule heating. In this study, we adopt this new artificial muscle to actuate a novel designed robotic manipulator, which is composed of two parts. The first part is a robotic arm based on the inspiration of the musculoskeletal system. The arm is fabricated with two ball-and-socket joints as skeleton and SCP actuators as driven muscles. The second part is a Fin Ray Effect inspired soft gripper that can perform grasping tasks on fragile objects. The manipulator prototype is fabricated and experimental tests are conducted including both simple but effective control of the bio-inspired arm as well as characterization of the gripper. Lastly, a pick and place demonstration of a fragile fruit is performed utilizing the proposed manipulator. We envision that the bio-inspired robotic manipulator design driven by SCP actuators could potentially be used in other robotic applications.

The widespread use of fluidic actuation for soft robots creates a high demand for soft pumps and compressors. However, current off-the-shelf pumps are usually rigid, noisy, and cumbersome. As a result, it is hard to integrate most commercial pumps into soft robotic systems, which restricts the autonomy and portability of soft robots. This paper presents the novel design of a soft pump based on bellow structure and super-coiled polymer (SCP) artificial muscles. The pump is flexible, lightweight, modular, scalable, quiet, and low cost. The pumping mechanism and fabrication process of the proposed soft pump is demonstrated. A pump prototype is fabricated to verify the proposed design and characterize its performance. From the characterization results, the pump can reach an output flow rate of up to 54 ml/min and delivers pressure up to 2.63 kPa. The pump has potential applications in untethered soft robots and wearable devices.

This article describes an innovative design of variable stiffness soft actuator, which can potentially be utilized for manipulation and locomotion of soft robots. The new actuator is a combination of two types of actuations: soft pneumatic actuation and muscle-like supercoiled polymer (SCP) actuation. Soft pneumatic actuator has two roles: first is to generate bending motions and second is to increase the stiffness of the whole actuator together with SCP artificial muscles. SCP artificial muscles are exploited to generate pre-load to resist the whole actuator from (excessive) deformation when external load is applied. These two types of actuations are arranged antagonistically to realize stiffness tuning of the whole actuator. At a given bending position, stiffness of the actuator could be tuned by controlling the pressure inside the air chamber and the tension on the SCP artificial muscles. In experimental section, tests are conducted to characterize the applied SCP artificial muscles before they are applied to the proposed actuator. Afterwards, tests of proposed actuator are performed to examine its variable stiffness capability. From experimental results, the proposed actuator can achieve 3.47 times stiffness variation ratio from 0.0312 N/mm(40kPa air pressure and no SCP actuation) to 0.1083 N/mm(82kPa air pressure and SCP actuation at 0.143 W/cm) at the same position (bending angle of 56 degree). This study exhibits the potential of applying SCP artificial muscles to promote the performance of soft robots.

The compliance of soft grippers contributes to their great superiority over rigid grippers in grasping irregularly shaped objects and forming soft contact with environments. Due to a relatively small pressure, soft grippers lack the stiffness required for wider applications. Particle jamming has been frequently reported as a means of stiffness control. Unlike previous research using vacuum for particle jamming, this paper proposes a novel passive particle jamming principle that does not need any vacuum power or other control means. The proposed method is by simply patching a silicone rubber soft actuator and a pack (made of strain-limiting membrane) of particles to form an integral gripping finger. The inflation of the soft actuator applies a pressure to the particle pack causing particles inside it to jam. A larger squeezing pressure will result in tighter particle jamming, thus increasing the stiffness of the finger. The stiffness of the finger is controllable as it is proportional to the actuator's air pressure, which has been verified by experiments in this research. The stiffness can increase more than six fold when air pressure changes from 20 to 80 kPa in the experimental studies. The reported discovery may enhance the capabilities of soft robotic grippers so that more robotic picking operations could be performed by soft grippers.

Shape memory polymer (SMP) is a type of functional materials that changes Young's modulus when heated above glass transition temperature (Tg). In this work, this property of SMP has been explored for the design and fabrication of a modular omni-directional joint with variable stiffness. When cascading a number of such joints, a variable stiffness hyper-redundant robotic arm can be built. The basic design of the variable stiffness joint is based on a ball joint where the ball is made of two materials: acrylonitrile butadiene styrene (ABS) and SMP, and the socket is made of only ABS material. When heated, the ball joint shows different resistive torques below and above the SMP's glass transition temperature Tg. Moreover, shape recovery property of SMP material above Tg guarantees the design with high repeatability. Both the ball and the socket are made by a 3D printing process fused deposition modeling (FDM). The FDM fabrication of SMP is made possible by a novel process control method in the FDM process. The ball joint's variable stiffness is tested by a number of experiments. Experimental results indicate distinct changes in resistive torques at different test temperatures. Using the proposed modular omni-directional ball joints, a variable stiffness hyper-redundant robotic arm is built.