ROFeb 14, 2022
Hybrid Soft Robots Incorporating Soft and Stiff ElementsDimuthu D. K. Arachchige, Isuru S. Godage
Soft robots are inherently compliant and have a strong potential to realize human-friendly and safe robots. Despite continued research highlighting the potential of soft robots, they remain largely confined to laboratory settings. In this work, inspired by spider monkeys' tails, we propose a hybrid soft robot (HSR) design. We detail the design objectives and methodology to improve the controllable stiffness range and achieve independent stiffness and shape control. We extend the curve parametric approach to We experimentally demonstrate that the proposed HSR has about a 100% stiffness range increase than a previous soft robot design with identical physical dimensions. In addition, we empirically map HSR's bending shape-pressure-stiffness and present an application example - a soft robotic gripper - to demonstrate the decoupled nature of stiffness and shape variations. Experimental results show that proposed HSR can be successfully used in applications where independent stiffness and shape control is desired.
ROOct 11, 2021
Dynamic Control of Soft Robotic ArmMilad Azizkhani, Isuru S. Godage, Yue Chen
In this article, the control problem of one section pneumatically actuated soft robotic arm is investigated in detail. To date, extensive prior work has been done in soft robotics kinematics and dynamics modeling. Proper controller designs can complement the modeling part since they are able to compensate other effects that have not been considered in the modeling, such as the model uncertainties, system parameter identification error, hysteresis, etc. In this paper, we explored different control approaches (kinematic control, PD+feedback linearization, passivity control, adaptive passivity control) and summarized the advantages and disadvantages of each controller. We further investigated the robot control problem in the practical scenarios when the sensor noise exists, actuator velocity measurement is not available, and the hysteresis effect is non-neglectable. Our simulation results indicated that the adaptive passivity control with sigma modification terms, along with a high-gain observer presents a better performance in comparison with other approaches. Although this paper mainly presented the simulation results of various controllers, the work will pave the way for practical implementation of soft robot control.
ROOct 22, 2020
Modeling and Validation of Soft Robotic Snake LocomotionDimuthu D. Arachchige, Yue Chen, Isuru S. Godage
Snakes are a remarkable evolutionary success story. Many snake-inspired robots have been proposed over the years. Soft robotic snakes (SRS) with their continuous and smooth bending capability better mimic their biological counterparts' unique characteristics. Prior SRSs are limited to planar operation with a limited number of planar gaits. We propose a novel SRS with spatial bending and investigate snake locomotion gaits beyond the capabilities of the state-of-the-art systems. We derive a complete floating-base kinematic model of the robot and use the model to derive jointspace trajectories for serpentine and inward/outward rolling locomotion gaits. The locomotion gaits for the proposed SRS are experimentally validated under varying frequency and amplitude of gait cycles. The results qualitatively and quantitatively validate the SRS ability to leverage spatial bending to achieve locomotion gaits not possible with current SRS.
ROOct 22, 2020
A Novel Variable Stiffness Soft Robotic GripperDimuthu D. Arachchige, Yue Chen, Ian D. Walker et al.
We propose a novel tri-fingered soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers adaptively conform to object shapes facilitating the handling of objects of different types, shapes, and sizes. Each soft gripper finger has an inextensible articulable backbone and is actuated by pneumatic muscles. We derive a kinematic model of the gripper and use an empirical approach to map input pressures to stiffness and bending deformation of fingers. We use these mappings to achieve decoupled stiffness and shape control. We conduct tests to quantify the ability to hold objects as the gripper changes orientation, the ability to maintain the grasping status as the gripper moves, and the amount of force required to release the object from the gripped fingers, respectively. The results validate the proposed gripper's performance and show how stiffness control can improve the grasping quality.
ROAug 14, 2019
Swimming locomotion of Soft Robotic SnakesIsuru S. Godage
Bioinspired snake robotics has been a highly active area of research over the years and resulted in many prototypes. Much of these prototypes takes the form of serially jointed-rigid bodies. The emergence of soft robotics contributed to a new type of snake robots made from compliant and structurally deformable modules. Leveraging the controllable large bending, these robots can naturally generate various snake locomotion gaits. Here, we investigate the swimming locomotion of soft robotic snakes. A numerically efficient dynamic model of the robot is first derived. Then, a distributed contact modal is augmented to incorporate hydrodynamic forces. The model is then numerically tested to identify the optimal bending propagation for efficient swimming. Results show that the soft robotic snakes have high potential to be used in marine applications.
ROJul 15, 2019
Forward and Inverse Kinematics of a Single Section Inextensible Continuum ArmAli A. Nazari, Diego Castro, Isuru S. Godage
Continuum arms, such as trunk and tentacle robots, lie between the two extremities of rigid and soft robots and promise to capture the best of both worlds in terms of manipulability, dexterity, and compliance. This paper proposes a new kinematic model for a novel constant-length continuum robot that incorporates both soft and rigid elements. In contrast to traditional pneumatically actuated, variable-length continuum arms, the proposed design utilizes a hyper-redundant rigid chain to provide extra structural strength. The proposed model introduces a reduced-order mapping to account for mechanical constraints arising from the rigid-linked chain to derive a closed-form curve parametric model. The model is numerically evaluated and the results show that the derived model is reliable.
ROJan 6, 2019
Center of Gravity-based Approach for Modeling Dynamics of Multisection Continuum ArmsIsuru S. Godage, Robert J. Webster, Ian D. Walker
Multisection continuum arms offer complementary characteristics to those of traditional rigid-bodied robots. Inspired by biological appendages, such as elephant trunks and octopus arms, these robots trade rigidity for compliance, accuracy for safety, and therefore exhibit strong potential for applications in human-occupied spaces. Prior work has demonstrated their superiority in operation in congested spaces and manipulation of irregularly-shaped objects. However, they are yet to be widely applied outside laboratory spaces. One key reason is that, due to compliance, they are difficult to control. Sophisticated and numerically efficient dynamic models are a necessity to implement dynamic control. In this paper, we propose a novel, numerically stable, center of gravity-based dynamic model for variable-length multisection continuum arms. The model can accommodate continuum robots having any number of sections with varying physical dimensions. The dynamic algorithm is of O(n2) complexity, runs at 9.5 kHz, simulates 6-8 times faster than real-time for a three-section continuum robot, and therefore is ideally suited for real-time control implementations. The model accuracy is validated numerically against an integral-dynamic model proposed by the authors and experimentally for a three-section, pneumatically actuated variable-length multisection continuum arm. This is the first sub real-time dynamic model based on a smooth continuous deformation model for variable-length multisection continuum arms.
RODec 13, 2018
Information Processing Capability of Soft Continuum ArmsEstefany A. Torres, Kohei Nakajima, Isuru S. Godage
Soft Continuum arms, such as trunk and tentacle robots, can be considered as the "dual" of traditional rigid-bodied robots in terms of manipulability, degrees of freedom, and compliance. Introduced two decades ago, continuum arms have not yet realized their full potential, and largely remain as laboratory curiosities. The reasons for this lag rest upon their inherent physical features such as high compliance which contribute to their complex control problems that no research has yet managed to surmount. Recently, reservoir computing has been suggested as a way to employ the body dynamics as a computational resource toward implementing compliant body control. In this paper, as a first step, we investigate the information processing capability of soft continuum arms. We apply input signals of varying amplitude and bandwidth to a soft continuum arm and generate the dynamic response for a large number of trials. These data is aggregated and used to train the readout weights to implement a reservoir computing scheme. Results demonstrate that the information processing capability varies across input signal bandwidth and amplitude. These preliminary results demonstrate that soft continuum arms have optimal bandwidth and amplitude where one can implement reservoir computing.
RODec 10, 2018
Near-optimal Smooth Path Planning for Multisection Continuum ArmsJiahao Deng, Brandon H. Meng, Iyad Kanj et al.
We study the path planning problem for continuum-arm robots, in which we are given a starting and an end point, and we need to compute a path for the tip of the continuum arm between the two points. We consider both cases where obstacles are present and where they are not. We demonstrate how to leverage the continuum arm features to introduce a new model that enables a path planning approach based on the configurations graph, for a continuum arm consisting of three sections, each consisting of three muscle actuators. The algorithm we apply to the configurations graph allows us to exploit parallelism in the computation to obtain efficient implementation. We conducted extensive tests, and the obtained results show the completeness of the proposed algorithm under the considered discretizations, in both cases where obstacles are present and where they are not. We compared our approach to the standard inverse kinematics approach. While the inverse kinematics approach is much faster when successful, our algorithm always succeeds in finding a path or reporting that no path exists, compared to a roughly 70% success rate of the inverse kinematics approach (when a path exists).
RONov 12, 2018
Dynamic Control of Pneumatic Muscle ActuatorsIsuru S. Godage, Yue Chen, Ian D. Walker
Pneumatic muscle actuators (PMA) are easy-to-fabricate, lightweight, compliant, and have high power-to-weight ratio, thus making them the ideal actuation choice for many soft and continuum robots. But so far, limited work has been carried out in dynamic control of PMAs. One reason is that PMAs are highly hysteretic. Coupled with their high compliance and response lag, PMAs are challenging to control, particularly when subjected to external loads. The hysteresis models proposed to-date rely on many physical and mechanical parameters that are difficult to measure reliably and therefore of limited use for implementing dynamic control. In this work, we employ a Bouc-Wen hysteresis modeling approach to account for the hysteresis of PMAs and use the model for implementing dynamic control. The controller is then compared to PID feedback control for a number of dynamic position tracking tests. The dynamic control based on the Bouc-Wen hysteresis model shows significantly better tracking performance. This work lays the foundation towards implementing dynamic control for PMA-powered high degrees of freedom soft and continuum robots.
RONov 12, 2018
Efficient Reduced-Order Models for Soft ActuatorsYue Chen, Kevin C. Galloway, Isuru S. Godage
Soft robotics have gained increased attention from the robotic community due to their unique features such as compliance and human safety. Impressive amount of soft robotic prototypes have shown their superior performance over their rigid counter parts in healthcare, rehabilitation, and search and rescue applications. However, soft robots are yet to capitalize on their potential outside laboratories and this could be attributed to lack of advanced sensing capabilities and real-time dynamic models. In this pilot study, we explore the use of high-accuracy, high-bandwidth deformation sensing via fiber optic strain sensing (FOSS) in soft bending actuators (SBA). Based on the high density sensor feedback, we introduce a reduced order kinematic model. Together with cubic spline interpolation, this model is able to reconstruct the continuous deformation of SBAs. The kinematic model is extended to derive an efficient real-time equation of motion and validated against the experimental data.