Hybrid Robotic System Research Articles

Self‐Sensing Artificial‐Muscle‐Empowered Humanlike Perception, Interaction, and Positioning

Bioinspired soft and hybrid robots provide a promising solution to developing robots that can interact and collaborate with humans safely and effectively. Bellow‐like pneumatic artificial muscles can produce biological muscle‐like contraction with comparable response time and force output, but closed‐loop control has been a challenge without an effective length sensing solution. Herein, a self‐sensing artificial muscle (SSAM), which can sense its own length regardless of the external loadings and driving pressures, is proposed. Empowered by a seamlessly integrated mutual‐inductance‐based length sensor (MILS), the SSAM can sense its length change as small as 0.01 mm (0.012% of the initial liength 80 mm) in a wide range. The working principle of the MILS is analyzed theoretically to provide a design guideline. An SSAM‐based earthworm‐like locomotion robot is developed with the capability of knowing its real‐time body length change at different gaits. An artificial arm driven by one SSAM is also developed and demonstrated with humanlike capabilities of loading perception, interactive and responsive movements, and accurate positioning. This work provides a promising solution to develop muscle‐driven hybrid robotic systems with embodied intelligence for skilled manipulation and sophisticated human–machine interactions.

Hybrid robotic systems

Standard laparoscopic instruments have limited dexterity because of their few degrees of freedom, making some surgical tasks extremely challenging. Robotic surgery was developed to overcome these issues, but the da Vinci system is associated with high costs. During recent years, many companies developed new robotic systems to improve dexterity and ergonomics with less impact on cost-effectiveness. This work describes the main commercially available modular robotic platforms, focusing on the technology, architecture and features, and advantages and disadvantages of each system. One of the main advantages of modular systems is the possibility of performing the whole procedure robotically or performing part of the procedure laparoscopically and part robotically as a hybrid approach. Next-generation robotic systems mainly include a modular design, open or semiopen consoles, smaller instruments, decreased cost, and augmented reality. To date, there are still few data in the literature comparing the systems, as many of them are awaiting regulatory approval. Thus, future studies are necessary to answer these questions. Many other robotic platforms are currently under development and will be available on the market, with a potential to alter surgical practice.

Motion Control of a Hybrid Quadruped-Quadrotor Robot

Multimodal motion capability is an emerging topic in the robotics field, and this paper presents a hybrid robot system maneuvering in both terrestrial and aerial environments. Firstly, a micro quadruped–quadrotor robot with onboard sensing and computing is developed. This robot incorporates both the high mobility of unmanned aerial vehicles and the long endurance of mobile robots on the ground. A coordinated motion control scheme is then exploited for adaptive terrestrial–aerial motion transition. In this scheme, a bio-inspired terrestrial locomotion controller is proposed to generate various quadruped locomotions, and a model-based aerial locomotion controller is proposed to generate various quadrotor configurations. Then, an unified motion controller for the two subsystems which dynamically adjusts crawling and flying motion in a complicated environment is presented. Consequently, several practical trials are conducted to demonstrate the adaptability and the robustness of the proposed system.

Design and Implementation of a Hybrid-Driven Soft Robot

Currently, soft robots alone cannot obtain the same operating speed as rigid robots, while rigid robots are not safe enough for human-robot interaction. To address this problem, this paper describes a hybrid robot system that combines both rigid and flexible systems for unknown domain exploration. The system consists of a four-wheeled robot chassis and a cylindrical pneumatic soft actuator, and finally, a computer is used to coordinate and control both. The hardware of the robot system is designed, a bending motion model is proposed, and SOFA framework is used to carry out finite element simulation (FEM) to verify the reasonableness of the design; linear motion speeds of up to 0.5 m/s, higher than the existing soft robots investigated, were verified experimentally separately after carrying the new module, and steering ability was retained; and the robot carrying the navigation module is verified to have a certain map building and localization function through the construction of the simultaneous localization and mapping (SLAM) experimental platform. The hybrid robot introduced in this paper can move quickly on flat terrain and can use its soft part to avoid wear and tear.

Adaptive neural network iterative learning control of long-stroke hybrid robots with initial errors and full state constraints

Research on initial errors and constraint restrictions is one of the main research directions in the field of control of uncertain robotic systems. An adaptive iterative learning control (AILC) method based on radial basis function (RBF) neural network is proposed to address the trajectory tracking problem of the long-stroke hybrid robot system with random initial errors and full state constraints. The RBF neural network is used to approximate the unknown nonlinear terms, and the network weights are updated using an iterative learning law that incorporates a projection mechanism. Additionally, a robust learning strategy is used to compensate for both the approximation error of the neural network and the external disturbances that vary with each iteration. To relax the requirement of traditional iterative learning control (ILC) for identical initial condition, an equivalent error function is constructed based on the time-varying boundary layer. The tangent-type barrier Lyapunov function (BLF) is designed to ensure that the joint position and speed of the robot system are bounded within a predetermined range. Through stability analysis based on barrier composite energy function (BCEF), it can be proved that the boundedness of all signals in the closed-loop system and the tracking error of the robot system will converge to an adjustable residual set asymptotically. Finally, through simulation experiments conducted on the MATLAB platform, the results demonstrate that the method overcomes the random initial errors of the system effectively, ensures that the system satisfies the full-state constraints, and realizes high-precision trajectory tracking.

A hybrid robotic system for zygomatic implant placement based on mixed reality navigation

BackgroundsZygomatic implant (ZI) placement surgery is a viable surgical option for patients with severe maxillary atrophy and insufficient residual maxillary bone. Still, it is difficult and risky due to the long path of ZI placement and the narrow field of vision. Dynamic navigation is a superior solution, but it presents challenges such as requiring operators to have advanced skills and experience. Moreover, the precision and stability of manual implantation remain inadequate. These issues are anticipated to be addressed by implementing robot-assisted surgery and achieved by introducing a mixed reality (MR) navigation-guided hybrid robotic system for ZI placement surgery. MethodsThis study utilized a hybrid robotic system to perform the ZI placement surgery. Our first step was to reconstruct a virtual 3D model from preoperative cone-beam CT (CBCT) images. We proposed a series of algorithms based on coordinate transformation, which includes image-phantom registration, HoloLens-tracker registration, drill-phantom calibration, and robot-implant calibration, to unify all objects within the same coordinate system. These algorithms enable real-time tracking of the surgical drill's position and orientation relative to the patient phantom. Subsequently, the surgical drill is directed to the entry position, and the planned implantation paths are superimposed on the patient phantom using HoloLens 2 for visualization. Finally, the hybrid robot system performs the processed of drilling, expansion, and placement of ZIs under the guidance of the MR navigation system. ResultsPhantom experiments of ZI placement were conducted using 10 patient phantoms, with a total of 40 ZIs inserted. Out of these, 20 were manually implanted, and the remaining 20 were robotically implanted. Comparisons between the actual implanted ZI paths and the preoperatively planned ZI paths showed that our MR navigation-guided hybrid robotic system achieved a coronal deviation of 0.887 ± 0.213 mm, an apical deviation of 1.201 ± 0.318 mm, and an angular deviation of 3.468 ± 0.339° This demonstrates significantly better accuracy and stability than manual implantation. ConclusionOur proposed hybrid robotic system enables automated ZI placement surgery guided by MR navigation, achieving greater accuracy and stability compared to manual operations in phantom experiments. Furthermore, this system is expected to apply to animal and cadaveric experiments, to get a good ready for clinical studies.

Optimal Design of Lower Limb Rehabilitation System Based on Parallel and Serial Mechanisms

This paper presents the structure and model of a hybrid modular structure of a robotic system for lower limb rehabilitation. It is made of two modules identical in structure, including an active 3-PRRR manipulator for moving the patient’s foot and a passive orthosis based on the RRR mechanism for supporting the lower limb. A mathematical model has been developed to describe the positions for the links of the active and passive mechanisms of two modules, as a function of the angles in the joints of the passive orthosis, considering constraints for attaching the active manipulators to the moving platform and their configurations. A method has been formulated for a parametric synthesis of the hybrid robotic system proposed with modular structure, taking into account the generated levels of parametric constraints depending on the ergonomic and manufacturability features. The proposed design is based on a criterion in the form of a convolution, including two components, one of which is based on minimizing unattainable points of the trajectory, considering the characteristics of anthropometric data, and the other is based on the compactness of the design. The results of the mathematical modeling are discussed as well as the analysis results towards a prototype validation.

Advanced materials for micro/nanorobotics.

Autonomous micro/nanorobots capable of performing programmed missions are at the forefront of next-generation micromachinery. These small robotic systems are predominantly constructed using functional components sourced from micro- and nanoscale materials; therefore, combining them with various advanced materials represents a pivotal direction toward achieving a higher level of intelligence and multifunctionality. This review provides a comprehensive overview of advanced materials for innovative micro/nanorobotics, focusing on the five families of materials that have witnessed the most rapid advancements over the last decade: two-dimensional materials, metal-organic frameworks, semiconductors, polymers, and biological cells. Their unique physicochemical, mechanical, optical, and biological properties have been integrated into micro/nanorobots to achieve greater maneuverability, programmability, intelligence, and multifunctionality in collective behaviors. The design and fabrication methods for hybrid robotic systems are discussed based on the material categories. In addition, their promising potential for powering motion and/or (multi-)functionality is described and the fundamental principles underlying them are explained. Finally, their extensive use in a variety of applications, including environmental remediation, (bio)sensing, therapeutics, etc., and remaining challenges and perspectives for future research are discussed.

Integrated system architecture with mixed-reality user interface for virtual-physical hybrid swarm simulations

This paper introduces a hybrid robotic swarm system architecture that combines virtual and physical components and enables human–swarm interaction through mixed reality (MR) devices. The system comprises three main modules: (1) the virtual module, which simulates robotic agents, (2) the physical module, consisting of real robotic agents, and (3) the user interface (UI) module. To facilitate communication between the modules, the UI module connects with the virtual module using Photon Network and with the physical module through the Robot Operating System (ROS) bridge. Additionally, the virtual and physical modules communicate via the ROS bridge. The virtual and physical agents form a hybrid swarm by integrating these three modules. The human–swarm interface based on MR technology enables one or multiple human users to interact with the swarm in various ways. Users can create and assign tasks, monitor real-time swarm status and activities, or control and interact with specific robotic agents. To validate the system-level integration and embedded swarm functions, two experimental demonstrations were conducted: (a) two users playing planner and observer roles, assigning five tasks for the swarm to allocate the tasks autonomously and execute them, and (b) a single user interacting with the hybrid swarm consisting of two physical agents and 170 virtual agents by creating and assigning a task list and then controlling one of the physical robots to complete a target identification mission.

SoRoSim: A MATLAB Toolbox for Hybrid Rigid–Soft Robots Based on the Geometric Variable-Strain Approach

Soft robotics has been a trending topic within the robotics community for almost two decades. However, available tools for the modeling and analysis of soft robots are still limited. This paper introduces a user-friendly MATLAB toolbox, Soft Robot Simulator (SoRoSim), that integrates the Geometric Variable Strain (GVS) model of Cosserat rods to facilitate the static and dynamic analysis of soft, rigid, or hybrid robotic systems. We present a brief overview of the design and structure of the toolbox and validate it by comparing its results with those published in the literature. To highlight the toolbox's potential to efficiently model, simulate, optimize, and control various robotic systems, we demonstrate four sample applications. The demonstrated applications explore different actuator and external loading conditions of single-, branched-, open-, and closed-chain robotic systems. We think that the soft-robotics research community will significantly benefit from the SoRoSim toolbox for a wide variety of applications.

Improving the method of controlling the search for surface and underwater objects by a hybrid robotic complex

One of the important scientific tasks of organising the control of searching for surface and underwater objects is to ensure the efficiency and trouble-free movement of a hybrid robotic complex in the modes of transition and search operation. An analysis of modern methods of controlling the search for surface and underwater objects by robotic vehicles in search operations, scientific and environmental research, monitoring, inspection and military underwater operations shows the need to use hybrid robotic systems. As part of the intellectualisation of the route planning process, it is relevant to solve the problem of synthesising an optimal trajectory to ensure that the search is carried out in all designated areas of the operation. The paper solves the problem of organising the management of searching for surface and underwater objects by a hybrid robotic complex, namely, building a route in the area of interest as an optimal spline trajectory of a moving object. The possibility of constructing a navigation function through the effective use of the curvature of the spline trajectory as a reproductive template for constructing an axonometric projection is determined. To accomplish this task, the paper improves the method of controlling the search for surface and underwater objects by a hybrid robotic complex by formalising the processes of planning the route of the hybrid robotic complex and the processes of information processing, forecasting the navigation situation and choosing a strategy for preventing dangerous situations by combining intelligent and numerical methods. The developed algorithm for constructing a search route for a hybrid robotic complex allows automated formation of spline trajectories in real time with synchronous submission of information about the parameters of the route to the control system of the hybrid robotic complex. This approach makes it possible to automate the search operation process and apply it in the CoCoRo and e-Navigation concepts

Application of hybrid robotic systems in crop harvesting: Kinematic and dynamic analysis

Harvesting of agricultural crops, especially when the ripe products have to be picked one by one, has always been a major concern of farmers and growers. Consequently, the use of robots and the mechanization of harvesting operations have been considered as the effective means of tackling such challenges. In the present research, the use of hybrid robots (which combine open-loop and closed-loop manipulators) has been proposed for this purpose; because these robots help reduce the size of the workforce and thus slash the harvesting costs, and they also boost the speed and accuracy of harvesting operations. However, using this type of robots without paying attention to some important factors (e.g., using motors of optimal power at the actuated joints of a robot and choosing appropriate lengths for robot links) can have a substantial adverse effect on the manufacturing cost, working space and the effective functioning of such robots. So the main focus of this paper is on the kinematic and dynamic analysis of hybrid robotic systems. The main advantage of this research over similar works is the generality by which it describes the mechanical behavior of these robots; so that by using the recursive algorithms presented in this paper, all kinds of robots in the hybrid class can be analyzed. However, due to the complexity in the analysis of such systems, a hybrid robot consisting of three closed loops and one open loop was considered in this paper as a sample case study, so that we could explain, visually and graphically, all the steps involved in deriving its motion equations. The simulation results for this robotic system demonstrate the efficacy of the proposed method in the kinematic and dynamic analysis of hybrid robots, as efficient and functional crop harvesting equipment.

Configurations and Applications of Multi-Agent Hybrid Drone/Unmanned Ground Vehicle for Underground Environments: A Review

Subterranean openings, including mines, present a unique and challenging environment for robots and autonomous exploration systems. Autonomous robots that are created today will be deployed in harsh and unexplored landscapes that humanity is increasingly encountering in its scientific and technological endeavors. Terrestrial and extraterrestrial environments pose significant challenges for both humans and robots: they are inhospitable and inaccessible to humans due to a lack of space or oxygen, poor or no illumination, unpredictable terrain, a GPS-denied environment, and a lack of satellite imagery or mapping information of any type. Underground mines provide a good physical simulation for these types of environments, and thus, can be useful for testing and developing highly sought-after autonomous navigation frameworks for autonomous agents. This review presents a collective study of robotic systems, both of individual and hybrid types, intended for deployment in such environments. The prevalent configurations, practices for their construction and the hardware equipment of existing multi-agent hybrid robotic systems will be discussed. It aims to provide a supplementary tool for defining the state of the art of coupled Unmanned Ground Vehicle (UGV)–Unmanned Aerial Vehicle (UAV) systems implemented for underground exploration and navigation purposes, as well as to provide some suggestions for multi-agent robotic system solutions, and ultimately, to support the development of a semi-autonomous hybrid UGV–UAV system to assist with mine emergency responses.

Right Hemicolectomy with Complete Mesocolic Excision Using the Versius Surgical System: A Step-by-Step Guide.

The application of new robotic platforms in colorectal surgery has increased greatly in the last 10 years. New systems have been released and entered the surgical panorama, broadening the technological offer. Robotic surgery applied to colorectal oncological surgery has been widely described. Hybrid robotic surgery in right sided colonic cancer has been previously reported. According to the site and local extension of a right-sided colon cancer, a different lymphadenectomy could be required. For more distant and locally advanced tumors a complete mesocolic excision (CME) is indicated. CME for right colon cancer is a complex operation compared to standard right hemicolectomy. Therefore a hybrid robotic system may be effectively applied to CME during a minimally-invasive right hemicolectomy to improve the dissection accuracy. Here we report a step-by-step hybrid laparoscopic/robotic right hemicolectomy with CME performed with the Versius Surgical System, a tele-operated surgical robotic system intended for the use of robotic assisted surgery.

Methodology for Selecting the Appropriate Electric Motor for Robotic Modular Systems for Lower Extremities.

Torque calculation is essential for selecting the appropriate motor to achieve the required torque at each joint of a hybrid exoskeleton. In recent years, the combined use of functional electrical stimulation (FES) and robotic devices, called hybrid robotic rehabilitation systems, has emerged as a promising approach for the rehabilitating of lower limb motor functions. Specifically, the implementation strategy of functional electrical stimulation walking aid combined with the design of the exoskeleton part is the main focus of our research team. This work copes with issues of the design process of a robotic exoskeleton. The importance of robotic exoskeletons for providing walking aid to people with mobility disorders or the elderly is discussed. Furthermore, the approaches to calculating the joint torques are investigated, and the mathematical models and parameters of interest are identified. This further includes the comparative data for servo motors: robotic exoskeleton characteristics and actuator analysis in the robotic exoskeleton. The aforementioned is used to propose a mathematical model based on previous models (Zatsiorsky BSP and Dempster BSP body segment parameters models, forward kinematics models), which was extended to include added adjustable parameters such as length, area, volume, mass, density, the centre of mass, human body characteristics, and considering both static and dynamic parameter extraction. Then, an analytic method is presented, exploiting the results from the mathematical model to select the appropriate motor for each joint of the lower extremities. The detailed description of the method is followed by examples, experimental measurements, and statistical analysis of qualitative and quantitative characteristics. The results showed deviations from typical calculation methods, offering a better understanding of the motor requirements for each joint of the exoskeleton and avoiding selections of marginal functionality features of the motors. In addition, researchers are offered a tool for replicating the results of this work, allowing them to configure the parameters associated with the servo motor features. The researcher can either use the embedded library developed for this work or enter new data into it, affecting the calculated torques of the model joints. The extracted results assist the researcher in choosing the appropriate motor among commercially available brushed and brushless motors based on the torques applied at each joint in robotic articulated systems.

The accuracy of a novel image-guided hybrid robotic system for dental implant placement: An in vitro study.

This in vitro study aims to evaluate the accuracy of dental implant placement by a novel image-guided hybrid robotic system for dental implant surgery (HRS-DIS). The HRS-DIS with a 5 degree of freedom (DOF) serial manipulator and a 6 DOF Stewart platform was developed. To evaluate the accuracy of repeated drilling, the holes were prepared twice with a 2.2mm drill. To evaluate the accuracy of dental implant placement, the entry, exit and angle deviations of dental implants were measured. Twenty-four holes were prepared twice, and mean (±SD) of diameters were measured as 2.2±0.02mm. A total of 160 dental implants were placed in 32 phantoms by HRS-DIS. The mean (±SD) of the entry, exit and angle deviation were 0.8±0.54mm, 0.87±0.54mm and 1.0 1±0.44°, respectively. The results of the in vitro study preliminarily validated that the HRS-DIS could provide a high accuracy for dental implant surgery.

Preliminary evaluation of a novel vision-guided hybrid robot system for capsulotomy in cataract surgery☆☆

Capsulotomy in cataract surgery is delicate and susceptible to surgeon fatigue, limited perception accuracy, and physiological hand tremors. To aid cataract surgery, we propose a novel vision-guided hybrid robot system. The robot, consisting of a PPRR/PPRRP parallel unit and an RP serial unit (R: rotation pair, P: prismatic pair), adopts a parallel configuration as the base. Capsulotomy has high requirements for position accuracy, thus, a robot control algorithm with the RCM constraint is proposed. This algorithm reduces the position error of the robot by limiting the position error within tolerance, thereby increasing the motion accuracy and smoothing the trajectory. Instead of obtaining position information based on the visual perception of the surgeons, we propose an edge detection method based on the U-Net to provide visual feedback to the robot.Experimental validations on a standard circle and ex-vivo pig eyeballs are performed to verify the effectiveness of the proposed robot control algorithm with the RCM constraint and the accuracy of the proposed robot system. When a circular trajectory of 5 mm is tracked, the maximum position error of the actuator end point is 0.084 mm and that of the RCM point is 0.292 mm. When the edge of the anterior capsule is tracked, the mean tracking error of the robot is 0.129 mm and that of the doctor is 0.764 mm.

Accuracy of dental implant surgery using dynamic navigation and robotic systems: An in vitro study

ObjectivesTo compare the accuracy of dental implant placement using a dynamic navigation and a robotic system. MethodsEighty three-dimensional (3D) printed phantoms, including edentulous and partially edentulous jaws, were assigned to two groups: a dynamic navigation system (Beidou-SNS) group and a robotic system (Hybrid Robotic System for Dental Implant Surgery, HRS-DIS) group. The entry, exit and angle deviations of the implants in 3D world were measured after pre-operative plans and postoperative cone-beam computed tomography (CBCT) fusion. A linear mixed model with a random intercept was applied, and a p value <.05 was considered statistically significant. ResultsA total of 480 implants were placed in 80 phantoms. The comparison deviation of the dynamic navigation system and robotic system groups showed a mean (± SD) entry deviation of 0.96 ± 0.57 mm vs. 0.83 ± 0.55 mm (p=0.04), a mean exit deviation of 1.06 ± 0.59 mm vs. 0.91 ± 0.56 mm (p=0.04), and a mean angle deviation of 2.41± 1.42° vs. 1 ± 0.48° (p<0.00). ConclusionsThe implant positioning accuracy of the robotic system was superior to that of the dynamic navigation system, suggesting that this prototype robotic system (HRS-DIS) could be a promising tool in dental implant surgery. Clinical significanceThis in vitro study is of clinical interest because it preliminarily shows that a robotic system exhibits lower deviations of dental implants than a dynamic navigation system, in dental implant surgery, in both partially and completely edentulous jaws. Further clinical studies are needed to evaluate the current results.

An image-guided hybrid robot system for dental implant surgery.

Dental implant surgery is an effective method for remediating the loss of teeth. Robot is expected to increase the accuracy of dental implant surgery. However, most of them are industrial serial robot, with low stiffness and non-unique inverse kinematic solution, which may reduce the success rate and safety of robotic surgery. Compared to serial robot, parallel robot is more stiffness and has unique inverse kinematic. However, its workspace is small, which may not meet surgical requirements. Therefore, a novel hybrid robot dedicated to dental implant is proposed. The hybrid robot is composed of three translation joints, two revolute joints, and Stewart parallel manipulator. Stewart is used for performing surgical operation, while the joints are used for enlarging the workspace of Stewart. In order to ensure the safety of robot motion, physical human-robot interaction based on a variable admittance controller is applied in the robotic system. In addition, considering the small workspace of Stewart, an optimal model is proposed to minimize the joint movement of Stewart in adjusting the orientation of drill bit. Phantom experiments were carried out based on the prototype robot. In the experiments, the optimal model could be solved after 20 iterations, finding an ideal joint configuration. The proposed variable admittance controller could enhance comfort level effectively. The accuracy of robot is evaluated by angle, entry and exit deviation, which are 0.74 ± 0.25°, 0.93 ± 0.28mm, and 0.96 ± 0.23mm, respectively. The phantom experiments validate the functionality of the proposed hybrid robot. The satisfactory performance makes it more widely used in the practical dental implant surgery in the future.

Biohybrid soft robots with self-stimulating skeletons.

Bioinspired hybrid soft robots that combine living and synthetic components are an emerging field in the development of advanced actuators and other robotic platforms (i.e., swimmers, crawlers, and walkers). The integration of biological components offers unique characteristics that artificial materials cannot precisely replicate, such as adaptability and response to external stimuli. Here, we present a skeletal muscle-based swimming biobot with a three-dimensional (3D)-printed serpentine spring skeleton that provides mechanical integrity and self-stimulation during the cell maturation process. The restoring force inherent to the spring system allows a dynamic skeleton compliance upon spontaneous muscle contraction, leading to a cyclic mechanical stimulation process that improves the muscle force output without external stimuli. Optimization of the 3D-printed skeletons is carried out by studying the geometrical stiffnesses of different designs via finite element analysis. Upon electrical actuation of the muscle tissue, two types of motion mechanisms are experimentally observed: directional swimming when the biobot is at the liquid-air interface and coasting motion when it is near the bottom surface. The integrated compliant skeleton provides both the mechanical self-stimulation and the required asymmetry for directional motion, displaying its maximum velocity at 5 hertz (800 micrometers per second, 3 body lengths per second). This skeletal muscle-based biohybrid swimmer attains speeds comparable with those of cardiac-based biohybrid robots and outperforms other muscle-based swimmers. The integration of serpentine-like structures in hybrid robotic systems allows self-stimulation processes that could lead to higher force outputs in current and future biomimetic robotic platforms.