Optoelectronically Innervated Suction Cup Inspired by the Octopus

With the emerging sector of new industrial age is afoot, innovations are made every day in order to cope with new technologies. Maintenance and regular repairs are key roles in keeping the industry as efficient as possible. With maintenance, safety is paramount in order to prevent accidents and further delays in production. In order to tackle issues for inspecting hazardous and tight spaces, this study utilizes soft robotics technology in aiming to achieve an efficient and cost-effective means to safely inspect tight and hazardous spaces. Soft Robotics is a field in robotics that specializes in materials that are flexible and elastic. Their movements mimic movements that are often found in nature. The soft robotic arm that will be accomplished in this study is a soft robotic tentacle arm with a mounted camera for inspection. This is especially good in reaching places that have limited spaces. The soft robotic arm will be actuated pneumatically and will have an electronic pneumatic microcontroller for its activation. A minicamera will also be mounted on the tip of the robotic arm for the inspection system. With the results and data gathered, it shows that this system can effectively maneuver using its electronic pneumatic controllers. The soft robot arm is also stable enough for the mini camera to be mounted on.

Designing and manufacturing actuators using soft materials are among the most important subjects for future robotics. In nature, animals made by soft tissues such as the octopus have attracted the attention of the robotics community in the last years. Suckers (or suction cups) are one of the most important and peculiar organs of the octopus body, giving it the ability to apply high forces on the external environment. The integration of suction cups in soft robots can enhance their ability to manipulate objects and interact with the environment similarly to what the octopus does. However, artificial suction cups are currently actuated using fluid pressure so most of them require external compressors, which will greatly increase the size of the soft robot. In this work, we proposed the use of the ElectroHydroDynamics (EHD) principle to actuate a suction cup. EHD is a fluidic phenomenon coupled with electrochemical reaction that can induce pressure through the application of a high-intensity electric field. We succeeded in developing a suction cup driven by EHD keeping the whole structure extremely simple, fabricated by using a 3D printer and a cutting plotter. We can control the adhesion of the suction cup by controlling the direction of the fluidic flow in our EHD pump. Thanks to a symmetrical arrangement of the electrodes, composed by plates parallel to the direction of the channel, we can change the direction of the flow by changing the sign of the applied voltage. We obtained the pressure of 643 Pa in one unit of EHD pump and pressure of 1428 Pa in five units of EHD pump applying 6 kV. The suction cup actuator was able to hold and release a 2.86 g piece of paper. We propose the soft actuator driven by the EHD pump, and expand the possibility to miniaturize the size of soft robots.

Soft robots are challenging to model and control due to their poorly defined kinematics and nonlinear dynamics. Recently, Koopman operator theory has been shown capable of constructing control-oriented soft robot models from data. However, building these models requires extensive data collection and they do not necessarily generalize well outside of the training observations. This paper presents a more data-efficient and generalizable approach to soft robot modeling that first identifies a physics-based Koopman model then supplements it with a data-driven residual Koopman model. The resulting combined model is linear and thus compatible with real-time model-based control techniques such as Model Predictive Control (MPC). The efficacy of the approach is demonstrated on several simulated systems and on a real soft robot arm, where it is shown to generate models that are more accurate than purely physics-based models and require less data to construct than purely data-driven models. Using a model-based controller, the soft arm is able to successfully track end effector trajectories, perform a pick-and-place task, and write on a dry-erase board, showcasing the applicability of this framework to increase the capabilities of soft robotic systems.

Suction cups are widely used in pick and place tasks in well-structured and controlled environments with low variance in task requirements. For tasks requiring higher demands and variations, such as quality control of citrus fruits, commercial suction cups do not have the required reliability. The design and performance of a novel suction cup based on particle jamming is presented in this paper. Particle jamming allows operation in two states, a malleable state to adapt to large irregularities in object surfaces, and a stiff state to rigidly hold the object for manipulation and prevent the cup collapsing in on itself. This jamming cup is shown to successfully adapt to surfaces with up to 7 times variations compared to standard suction cups. Additionally, for similar scale cups, the holding force is comparable and has <50% deviation.

Inherent compliance equips soft robotic arms with such advantages as incomparable flexibility, good adaptability, and safe interaction with the environment, etc. However, the strong nonlinearity also brings challenges to predict their dynamic behaviors. This work presents a simplified dynamic model of an underwater soft robotic arm which has three fiber-reinforced hydraulic chambers distributed symmetrically in each section. By controlling the pressures in the chambers, the soft robotic arm can perform complex spatial motion with multiple degrees of freedom. The model is based on Lagrangian method and piecewise constant curvature hypothesis, and considers the nonlinear viscoelasticity of soft material. The model accuracy is verified by the experiments of a two-section soft robotic arm with different actuation modes. The effects of geometrical features on dynamic response are also investigated through model-based simulation and test verification, which can provide guidance to parameter optimization. The proposed dynamic model can be extended to multiple sections and contribute to behavior analysis, performance prediction, and motion control of the soft robotic arm.

Commercial suction cups offer versatile solutions for adhering to a variety of objects through their good adhesion capabilities, compliance to object features, and ease of use. This has made them a practical solution for a variety of applications, and they have become ubiquitous across diverse industries. However, they are limited in their ability to adhere to objects at an angle from their main axis due to the limited passive compliance of their structure. This study introduces morphing suction cups that use cavities within the walls of the suction cups to enable them to bend and lengthen while still allowing the suction cup to adhere to objects. The morphing suction was able to lengthen by 42.7% of its initial length and bend at an angle of up to 67°. This allowed to adhere to objects at an angle of up to 70° from the axis of the suction cup. A multi-directional morphing suction cup was also presented which can bend bidirectionally. The proposed morphing suction cup has the potential to increase the versatility of suction cups for unstructured environments.

Controlling soft robots is a significant challenge due to the nonlinear elastic nature of the soft materials that conform their structure. This paper studies the identification and control problems of a novel two-degrees-of-freedom, tendon-actuated, soft robotic arm. A decoupled identification approach is presented; later, a fractional order control strategy is proposed and tested experimentally, in comparison with PI solutions. The simulation and experimental results show the goodness of the modeling and control approaches discussed.

To improve the adaptability of soft robots to the environment and achieve reliable attachment on various surfaces such as smooth and rough, this study draws inspiration from the collaborative attachment strategy of insects, cats, and other biological claw hooks and foot pads, and designs an actuator with a bionic claw hook–suction cup hybrid structure. The rigid biomimetic pop-up claw hook linkage mechanism is combined with a flexible suction cup of a ‘foot pad’ to achieve a synergistic adhesion effect between claw hook locking and suction cup adhesion through the deformation control of a soft pneumatic actuator. A pop-up claw hook linkage mechanism based on the principle of cat claw movement was designed, and the attachment mechanism of the biological claw hooks and footpads was analysed. An artificial muscle-spring-reinforced flexible pneumatic actuator (SRFPA) was developed and a kinematic model of the SRFPA was established and analysed using Abaqus. Finally, a prototype of the hybrid actuator was fabricated. The kinematic and mechanical performances of the SRFPA and entire actuator were characterised, and the attachment performance of the hybrid actuator to smooth and rough surfaces was tested. The results indicate that the proposed biomimetic claw hook–suction cup hybrid structure actuator is effective for various types of surface adhesion, object grasping, and robot walking. This study provides new insights for the design of highly adaptable robots and biomimetic attachment devices.

Fluidic elastomer actuators have become ubiquitous in soft robotics as they can be used to create inherently compliant systems with embodied intelligence. However, they typically use conventional rigid air‐compression systems that restrict their application in untethered mobile and wearable devices. An embeddable pneumatic diaphragm pump is presented for soft robotics driven by a magnetically coupled dielectric elastomer actuator (MCDEA). The MCDEA pump exploits a compliant coupling between membranes to resonate at high power and efficiency despite the damping effects of the pneumatic chamber and valves. The MCDEA pump demonstrates an attractive dynamic performance with a peak stroke at resonance of over 800% of that at low frequencies, which corresponds to a maximum output pressure of 30.5 mbar and a flowrate of 0.9 L min−1 at a relatively low power consumption of 40 mW. The performance of this pneumatic pump design is demonstrated by integrating it with several soft robotic prototypes, including a soft gripper, ballooning chamber, and a suction cup. It shows considerable promise for driving the next generation of fully compliant and untethered soft robots.

Applying suction grippers in unstructured environments is a challenging task because of depth and tilt errors in vision systems, requiring additional costs in elaborate sensing and control. To reduce additional costs, suction grippers with compliant bodies or mechanisms have been proposed; however, their bulkiness and limited allowable error hinder their use in complex environments with large errors. Here, we propose a compact suction gripper that can pick objects over a wide range of distances and tilt angles without elaborate sensing and control. The spring-inserted gripper body deploys and conforms to distant and tilted objects until the suction cup completely seals with the object and retracts immediately after, while holding the object. This seamless deployment and retraction is enabled by connecting the gripper body and suction cup to the same vacuum source, which couples the vacuum picking and retraction of the gripper body. Experimental results validated that the proposed gripper can pick objects within 79 mm, which is 1.4 times the initial length, and can pick objects with tilt angles up to 60 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> . The feasibility of the gripper was verified by demonstrations, including picking objects of different heights from the same picking height and the bin picking of transparent objects.

Conventional suction cups lack sensing capabilities for contact-aware manipulation in unstructured environments. This paper presents FlexiCup, a multimodal suction cup with wireless electronics that integrate dual-zone vision-tactile sensing. The central zone dynamically switches between vision and tactile modalities via illumination control, while the peripheral zone provides continuous spatial awareness. The modular mechanical design supports both vacuum (sustained-contact adhesion) and Bernoulli (contactless lifting) actuation while maintaining the identical dual-zone sensing architecture, demonstrating sensing-actuation decoupling where sensing and actuation principles are orthogonally separable. We validate hardware versatility through dual control paradigms. Modular perception-driven grasping achieves comparable success rates across vacuum (90.0%) and Bernoulli (86.7%) modes using identical sensing and control pipelines, validating the sensing architecture's effectiveness across fundamentally different pneumatic principles. Diffusion-based end-to-end learning achieves 73.3% and 66.7% success on contact-aware manipulation tasks, with ablation studies confirming 13% improvements from multi-head attention coordinating dual-zone observations. Hardware designs, firmware, and experimental videos are available at the companion website: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://flexicup.junhaogong.top</uri>.

In recent years, soft robots gain increasing attention as a result of their compliance when operating in unstructured environments, and their flexibility that ensures safety when interacting with humans. However, challenges lie on the difficulty to develop control algorithms due to various limitations induced by their soft structure. In this paper, we introduce a novel technique that aims to perform motion control of a modular bio-inspired soft-robotic arm, with the main focus lying on facilitating the qualitative reproduction of well-specified periodic trajectories. The introduced method combines the notion behind two previously developed methodologies both based on the Movement Primitive (MP) theory, by exploiting their capabilities while coping with their main drawbacks. Concretely, the requested actuation is initially computed using a Probabilistic MP (ProMP)-based method that considers the trajectory as a combination of simple movements previously learned and stored as a MP library. Subsequently, the key components of the resulting actuation are extracted and filtered in the frequency domain. These are eventually used as input to a Central Pattern Generator (CPG)-based model that takes over the generation of rhythmic patterns at the motor level. The proposed methodology is evaluated on a two-module soft arm. Results show that the first algorithmic component (ProMP) provides an immediate estimation of the requested actuation by avoiding time-consuming training, while the latter (CPG) further simplifies the execution by allowing its control through a low-dimensional parameterization. Altogether, these results open new avenues for the rapid acquisition of periodic movements in soft robots, and their compression into CPG parameters for long-term storage and execution.

The paper focuses on design and control of a new anthropomorphic robot arm enabling the torque measurement in each joint to ensure safety while performing tasks of physical interaction with human and environment. When the contact of the arm with an object occurs, local impedance algorithm provides active compliance of corresponding robot arm joint. Thus, the whole structure of the manipulator can safely interact with unstructured environment. A novel variable control strategy was elaborated to increase the robot functionality and to achieve human-like dynamics of interaction. In the paper, we detail the design procedure of 4-DOF robot arm and optical torque sensors. The experimental results of variable joint impedance control show that proposed approach not only provides safe interaction of entire structure of robot arm with a person, but also improves the effectiveness of contact task performance, enables thus to contact with environment in a delicate manner.

Octopus show great adhesion capabilities thanks to their suckers covering their ventral side of their arms. Starting from biological investigation, we identified preliminary specifications for the design of innovative artificial suction cups, which could be used in the field of soft robotics. The main features of the biological sucker are maintained as leading criteria for the choice of the actuation technology and mechanism. In this preliminary work, we focused on the imitation of the functionality of the specific muscle bundles which generate suction to obtain adhesion. Dielectric Elastomers Actuators (DEA) were identified as a suitable solution. A study on materials and manufacturing techniques was made. Different possible solutions in the use of DEA are also described.

To perch on or grasp the objective surface using the suction cup-based manipulator, the precise contact control is commonly required. Improper contact angle or insufficient contact force may cause failure. To enhance the tolerance to flight control insufficiency, a suction cup that comprises an inner soft cup and an outer firm cup to facilitate its engagement without reducing the adhesion stiffness is investigated. The soft cup is adaptable to the angular error induced by the multicopter and the resulting adhesion force can draw the firm cup and correct the angular error between the firm cup and the surface. These effects increase the engagement rate and reduce the dependence on precise control. The outer firm cup is devoted to providing a large adhesion force and a stiff base for subsequent tasks. To reduce the air evacuation time in the firm cup, a novel self-sealing structure is designed. Based on the combined cup, we build a multifunctional aerial manipulation system which can execute perching or lateral aerial grasping tasks. With the proposed prototype, the comparative flight experiments involving perching on a wall under disturbance and grasping an object are conducted. The results demonstrate that our proposed suction cup outperforms the conventional cup.