Erik H. Skorina

Slithering towards autonomy: a self-contained soft robotic snake platform with integrated curvature sensing

Soft robotic snakes promise significant advantages in achieving traveling curvature waves with a reduced number of active segments as well as allowing for safe and adaptive interaction with the environment and human users. However, current soft robot platforms suffer from a lack of accurate theoretical dynamic models and proprioceptive measurements, which impede advancements toward full autonomy. To address this gap, this paper details our recent results on the design, fabrication, and experimental evaluation of a new-generation pressure-operated soft robotic snake platform we call the WPI SRS, which employs custom magnetic sensors embedded in a flexible backbone to continuously monitor the curvature of each of its four bidirectional bending segments. In addition, we present a complete and accurate dynamic undulatory locomotion model that accounts for the propagation of frictional moments to describe linear and rotational motions of the SRS. Experimental studies indicate that on-board sensory measurements provide accurate real-time curvature feedback, and numerical simulations offer a level of abstraction for lateral undulation under ideal conditions.

A composite soft bending actuation module with integrated curvature sensing

Soft robotics carries the promise of making robots as capable and adaptable as biological creatures, but this will not be possible without the ability to perform self-sensing and control with precision and repeatability. In this paper, we seek to address this need with the development of a new pneumatically-actuated soft bending actuation module with integrated curvature sensing. We designed and fabricated two different versions of this module: One with a commercially available resistive flex sensor and the other with a magnetic curvature sensor of our own design, and used an external motion capture system to calibrate and validate these two approaches. In addition, we used an iterative sliding mode controller to drive the modules through step curvature references to demonstrate the controllability of the modules as well as compare the usability of the two sensors. We found that the magnetic sensor returned noisy but accurate data, while the flex sensor had minor inaccuracies and it was subject to overshoot but did not exhibit notable noise. Experimental results show that this phenomenon of overshoot from the flex sensor causes active feedback control of the bending actuator to exhibit significant positioning errors. This work demonstrates that our soft bending actuator can be controlled with repeatability and precision, and that our magnetic curvature sensor represents an improvement for use in proprioception and closed-loop control of soft robotic devices.

Feedforward augmented sliding mode motion control of antagonistic soft pneumatic actuators

Soft pneumatic actuators provide many exciting properties, but controlling them without the use of bulky and expensive flow-control valves can be difficult and computationally expensive. We seek a solution to this problem by introducing an inexpensive and reliable muscle-like linear soft actuator used antagonistically to operate a rigid 1-DoF joint, resulting in a system that combines the advantages of rigid and soft robotics. Using this setup, we performed precise motion control using a sliding mode feedback controller as well as a sliding mode controller augmented by a feedforward term to modulate the state of solenoid valves that drive each actuator. We found that both controllers performed equivalently well in following a step function and in responding to a disturbance. The feedforward augmented controller performed significantly better when following dynamic trajectories over a range of frequencies and with the addition of an external force. The next step will be to modify our valve control scheme to allow for the determination of both the position and stiffness of the joint, better leveraging the advantages of soft pneumatic actuators.

Optimized design of a rigid kinematic module for antagonistic soft actuation

Soft actuators can be useful in human-occupied environments because of their adaptable compliance and light weight. We previously introduced a variation of fluidic soft actuators we call the reverse pneumatic artificial muscle (rPAM), and developed an analytical model to predict its performance both individually and while driving a 1 degree of freedom revolute joint antagonistically. Here, we expand upon this previous work, adding a correction term to improve model performance and using it to perform optimization on the kinematic module dimensions to maximize achievable joint angles. We also offer advances on the joint design to improve its ability to operate at these larger angles. The new joint had a workspace of around ±60°, which was predicted accurately by the improved model.

Motion control of a soft-actuated modular manipulator

Soft pneumatic actuators can allow robotic manipulators to interact safely in complex environments in close proximity to humans, but work still needs to be done controlling them more effectively. We explore this area by introducing a 2-degree of freedom (DoF) universal joint module actuated by three reverse Pneumatic Artificial Muscles (rPAMs) and an associated geometric Jacobian-enhanced iterative sliding mode controller. After demonstrating the effectiveness of this controller, we combine two of these modules to form a 4-DoF soft actuated manipulator. To control this modular manipulation system, we propose two controllers: a direct inverse kinematic (IK) controller and an end-effector geometric Jacobian controller. Though both controllers were validated to function effectively, the Jacobian controller was more precise (especially under payload) while the IK controller was more accurate.

Bioinspired design and fabrication principles of reliable fluidic soft actuation modules

A large percentage of the field of robotics is devoted to catching up to what nature can already do. Taking inspiration from the snake and the jumping spider, we describe advances towards standardized design and fabrication of modular multi-material composite soft pneumatic actuators. Previous pneumatic bi-directional bending actuators used in our soft robotic snake suffered from repeatability challenges and were prone to bursting in the seams. Here, we present a standardized fabrication method of soft pneumatic actuators to reduce the seams and incorporate a more reliable port for the input pressure. In addition, we explore the integration of our flexible curvature sensor, allowing for less invasive proprioceptive sensing of the actuator state. Finally, taking inspiration from jumping spider legs, we propose a plastic exoskeleton system, which can guide soft actuators to form complex shapes when pressurized. We show that all of these actuators were consistent and reliable over numerous trials. The next step is to combine these individual actuators into their respective bioinspired robotic systems: a soft modular snake and a soft jumping spider.

Adapting to Flexibility: Model Reference Adaptive Control of Soft Bending Actuators

Soft pneumatic actuators enable robots to interact safely with complex environments, but often suffer from imprecise control and unpredictable dynamics. This letter addresses these challenges through the use of model reference adaptive control, which modulates the input to the plant to ensure that it behaves similarly to a reference dynamic model. We use adaptive control to standardize the performance of soft actuators and eliminate their nonlinear behavior. We implement an adaptive controller chosen for its simplicity and efficiency, and study the ability of this controller to force different soft pneumatic actuators to behave uniformly under a variety of conditions. Next, we formulate an inverse dynamic feedforward controller, allowing soft actuators to quickly follow reference trajectories. We test the performance of the proposed feedforward controller with and without the adaptive controller, to study its open-loop effectiveness and highlight the improvements the adaptive controller offers. Our experimental results indicate that soft actuators can follow unstructured continuous signals through the use of the proposed adaptive control approach.

REFINED THEORETICAL MODELING OF A NEW-GENERATION PRESSURE-OPERATED SOFT SNAKE

Our pressure-operated soft snake robot promises inherent flexibility and versatility to operate on complex and unpredictable environments compared to traditional snake robots made of rigid linkage chains. We previously presented a theoretical framework to describe its unique dynamic behavior and experimentally verified the accuracy of this model. This previous work had some drawbacks; the maximum center of mass velocity of the previous soft snake was one tenth its body length per second and the dynamic model could not predict the behavior of the robot when following non-linear trajectories because of a lack of frictional torques. In this paper we introduce the next generation of our soft robotic snake we call the “WPI SRS”, which can locomote ten times faster than the previous version. Additionally, we present refinements to the dynamical model that can predict both linear and rotational motions of the robot. Finally, we demonstrate the accuracy of this refined model through experimentation.Copyright

Reverse pneumatic artificial muscles (rPAMs): Modeling, integration, and control

Despite offering many advantages over traditional rigid actuators, soft pneumatic actuators suffer from a lack of comprehensive, computationally efficient models and precise embedded control schemes without bulky flow-control valves and extensive computer hardware. In this article, we consider an inexpensive and reliable soft linear actuator, called the reverse pneumatic artificial muscle (rPAM), which consists of silicone rubber that is radially constrained by symmetrical double-helix threading. We describe analytical and numerical static models of this actuator, and compare their performance against experimental results. To study the application of rPAMs to operate underlying kinematic linkage skeletons, we consider a single degree-of-freedom revolute joint that is driven antagonistically by two of these actuators. An analytical model is then derived, and its accuracy in predicting the static joint angle as a function of input pressures is presented. Using this analytical model, we perform dynamic characterization of this system. Finally, we propose a sliding-mode controller, and a sliding mode controller augmented by a feed-forward term to modulate miniature solenoid valves that control air flow to each actuator. Experiments show that both controllers function well, while the feed-forward term improves the performance of the controller following dynamic trajectories.

A Soft Robotic Wearable Wrist Device for Kinesthetic Haptic Feedback

Advances in soft robotics provide a unique approach for delivering haptic feedback to a user by a soft wearable device. Such devices can apply forces directly on the human joints, while still maintaining the safety and flexibility necessary for use in close proximity to the human body. To take advantage of these properties, we present a new haptic wrist device using pressure-driven soft actuators called reverse pneumatic artificial muscles (rPAMs) mounted on four sides of the wrist. These actuators are originally pre-strained and release compressive stress under pressure, applying a safe torque around the wrist joints while being compact and portable, representing the first soft haptic device capable of real-time feedback. To demonstrate the functional utility of this device, we created a virtual path-following task, wherein the user employs the motion of their wrist to control their embodied agent. We used the haptic wrist device to assist the user in following the path and study their performance with and without haptic feedback in multiple scenarios. Our results quantify the effect of wearable soft robotic haptic feedback on user performance. Specifically, we observed that our haptic feedback system improved the performance of users following complicated paths in a statistically significant manner, but did not show improvement for simple linear paths. Based on our findings, we anticipate broader applications of wearable soft robotic haptic devices toward intuitive user interactions with robots, computers, and other users.