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1. Cable-Driven Jamming of a Boundary Constrained Soft Robot

   https://doi.org/10.1109/RoboSoft48309.2020.9116042  

   Tanaka, Koki; Karimi, Mohammad Amin; Busque, Bruno-Pier; Mulroy, Declan; Zhou, Qiyuan; Batra, Richa; Srivastava, Ankit; Jaeger, Heinrich M.; Spenko, Matthew (May 2020, 2020 3rd IEEE International Conference on Soft Robotics (RoboSoft))

   Soft robots employ flexible and compliant materials to perform adaptive tasks and navigate uncertain environments. However, soft robots are often unable to achieve forces and precision on the order of rigid-bodied robots. In this paper, we propose a new class of mobile soft robots that can reversibly transition between compliant and stiff states without reconfiguration. The robot can passively conform or actively control its shape, stiffen in its current configuration to function as a rigid-bodied robot, then return to its flexible form. The robotic structure consists of passive granular material surrounded by an active membrane. The membrane is composed of interconnected robotic sub-units that can control the packing density of the granular material and exploit jamming behaviors by varying the length of the interconnecting cables. Each robotic sub-unit uses a differential drive system to achieve locomotion and self-reconfigurability. We present the robot design and perform a set of locomotion and object manipulation experiments to characterize the robot's performance in soft and rigid states. We also introduce a simulation framework in which we model the jamming soft robot design and study the scalability of this class of robots. The proposed concept demonstrates the properties of both soft and rigid robots, and has the potential to bridge the gap between the two 

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2. Dynamic Control of Soft Robots with Internal Constraints in the Presence of Obstacles

   Cosimo Della Santina, Antonio Bicchi (October 2019, Internationa Symposium on Intelligent Robot Systems (IROS))

   The development of effective reduced order models for soft robots is paving the way toward the development of a new generation of model based techniques, which leverage classic rigid robot control. However, several soft robot features differentiate the soft-bodied case from the rigid-bodied one. First, soft robots are built to work in the environment, so the presence of obstacles in their path should always be explicitly accounted by their control systems. Second, due to the complex kinematics, the actuation of soft robots is mapped to the state space nonlinearly resulting in spaces with different sizes. Moreover, soft robots often include internal constraints and thus actuation is typically limited in the range of action and it is often unidirectional. This paper proposes a control pipeline to tackle the challenge of controlling soft robots with internal constraints in environments with obstacles. We show how the constraints on actuation can be propagated and integrated with geometrical constraints, taking into account physical limits imposed by the presence of obstacles. We present a hierarchical control architecture capable of handling these constraints, with which we are able to regulate the position in space of the tip of a soft robot with the discussed characteristics. 

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3. Body-Induced Soft Robotic Locomotion: a Sim-To-Real Approach

   https://doi.org/10.1109/UR65550.2025.11078082  

   Wang, Zhaosen; Mallikarachchi, Sanjaya; Arachchige, Dimuthu_D K; Perera, Dulanjana M; Thammi, Phanindrateja; Godage, Isuru S (June 2025, IEEE)

   Soft robots, valued for their compliance and deformable nature, have demonstrated their outstanding abilities in complex environments. However, the nonlinear dynamics make it challenging to derive efficient locomotion patterns from analytical methods. This is largely due to the high computational cost associated with simulating soft-bodied models. Conversely, rigid-body models, such as those used in Gazebo, offer computational efficiency but cannot directly represent soft robots. We address these challenges by introducing customized Gazebo plugins that enable the simulation and analysis of soft robot locomotion dynamics. These plugins are complemented by a novel JointStiffnessPlugin, integrated with ROS services, for fine-tuning effort-controlled parameters. The system identification process is followed to match the simulation dynamics with the real soft robot to minimize the sim-to-real gap. Utilizing the proposed simulation framework and Bayesian Optimization, we derived a body-induced locomotion strategy that achieves enhanced efficiency. This strategy, relying solely on periodic spine bending and robot pose for forward propulsion, demonstrably reduces energy consumption compared to conventional gaits. Experimental results confirm a 42 % energy expenditure reduction relative to four-legged crawling. 

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4. Mechanically Versatile Soft Machines through Laminar Jamming

   https://doi.org/10.1002/adfm.201707136  

   Narang, Yashraj_S; Vlassak, Joost_J; Howe, Robert_D (February 2018, Advanced Functional Materials)

   Abstract There are two major structural paradigms in robotics: soft machines, which are conformable, durable, and safe; and traditional rigid robots, which are fast, precise, and capable of applying high forces. Here, the paradigms are bridged by enabling soft machines to behave like traditional rigid robots on command. This task is accomplished via laminar jamming, a structural phenomenon in which a laminate of compliant strips becomes strongly coupled through friction when a pressure gradient is applied, causing dramatic changes in mechanical properties. Rigorous analytical and finite element models of laminar jamming are developed, and jamming structures are experimentally characterized to show that the models are highly accurate. Then jamming structures are integrated into soft machines to enable them to selectively exhibit the stiffness, damping, and kinematics of traditional rigid robots. The models allow jamming structures to efficiently meet arbitrary performance specifications, and the physical demonstrations illustrate how to construct systems that can behave like either soft machines or traditional rigid robots at will, such as continuum manipulators that can rapidly have joints appear and disappear. This study aims to foster a new generation of mechanically versatile machines and structures that cannot simply be classified as “soft” or “rigid.” 

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5. Information Processing Capability of Soft Continuum Arms

   https://doi.org/10.1109/ROBOSOFT.2019.8722777  

   Torres, Estefany; Nakajima, Kohei; Godage, Isuru S. (April 2019, 2019 2nd IEEE International Conference on Soft Robotics (RoboSoft))

   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. 

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