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1. Encoder-less Robot Control for Space Operations with Continuum Robots

   Frazaelle, C.G.; Walker, I.D.; AlAttar, A.; Kormushev, P. (March 2021, IEEE Aerospace Conference)

   null (Ed.)

   Continuum robots have strong potential for application in Space environments. However, their modeling is challenging in comparison with traditional rigid-link robots. The Kinematic-Model-Free (KMF) robot control method has been shown to be extremely effective in permitting a rigid-link robot to learn approximations of local kinematics and dynamics (“kinodynamics”) at various points in the robot’s task space. These approximations enable the robot to follow various trajectories and even adapt to changes in the robot’s kinematic structure. In this paper, we present the adaptation of the KMF method to a three-section, nine degrees-of-freedom continuum manipulator for both planar and spatial task spaces. Using only an external 3D camera, we show that the KMF method allows the continuum robot to converge to various desired set points in the robot’s task space, avoiding the complexities inherent in solving this problem using traditional inverse kinematics. The success of the method shows that a continuum robot can “learn” enough information from an external camera to reach and track desired points and trajectories, without needing knowledge of exact shape or position of the robot. We similarly apply the method in a simulated example of a continuum robot performing an inspection task on board the ISS. 

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2. Directional Stiffness-Switching Soft Robots via Phase-Changing Metallic Spines

   https://doi.org/10.1109/RoboSoft60065.2024.10521936  

   Esser, Daniel S; McCabe, Emily; Ertop, Tayfun Efe; Kuntz, Alan; Webster, Robert J (April 2024, IEEE International Conference on Soft Robotics (RoboSoft))

   Conventional soft robots are designed with constant, passive stiffness properties, based on desired motion capabilities. The ability to encode two fundamentally different stiffness characteristics promises to enable a single robot to be optimized for multiple divergent tasks simultaneously and this has been previously proposed with a variety of approaches including jamming-based designs. In this paper, we propose phase-changing metallic spines of various geometries to independently control specific directional stiffness parameters of soft robots, changing how they respond to their actuation inputs and external loads. We fabricate spine-like structures using a low melting point alloy (LMPA), enabling us to switch on and off the effects of the stiff metal structure of the overall robot's stiffness during use. Changing soft robot morphology in this manner will enable these robots to adapt to environments and tasks that require divergent motion and force/moment application capabilities. 

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3. Modular Design of a Polymer‐Bilayer‐Based Mechanically Compliant Worm‐Like Robot

   https://doi.org/10.1002/adma.202210409  

   Muff, Livius F; Mills, Austin S; Riddle, Shane; Buclin, Véronique; Roulin, Anita; Chiel, Hillel J; Quinn, Roger D; Weder, Christoph; Daltorio, Kathryn A (May 2023, Advanced Materials)

   Abstract Soft earthworm‐like robots that exhibit mechanical compliance can, in principle, navigate through uneven terrains and constricted spaces that are inaccessible to traditional legged and wheeled robots. However, unlike the biological originals that they mimic, most of the worm‐like robots reported to date contain rigid components that limit their compliance, such as electromotors or pressure‐driven actuation systems. Here, a mechanically compliant worm‐like robot with a fully modular body that is based on soft polymers is reported. The robot is composed of strategically assembled, electrothermally activated polymer bilayer actuators, which are based on a semicrystalline polyurethane with an exceptionally large nonlinear thermal expansion coefficient. The segments are designed on the basis of a modified Timoshenko model, and finite element analysis simulation is used to describe their performance. Upon electrical activation of the segments with basic waveform patterns, the robot can move through repeatable peristaltic locomotion on exceptionally slippery or sticky surfaces and it can be oriented in any direction. The soft body enables the robot to wriggle through openings and tunnels that are much smaller than its cross‐section. 

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4. 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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5. Model-based contact detection and position control of a fabric soft robot in unknown environments

   https://doi.org/10.3389/frobt.2022.997366  

   Qiao, Zhi; Nguyen, Pham H.; Zhang, Wenlong (October 2022, Frontiers in Robotics and AI)

   Soft robots have shown great potential to enable safe interactions with unknown environments due to their inherent compliance and variable stiffness. However, without knowledge of potential contacts, a soft robot could exhibit rigid behaviors in a goal-reaching task and collide into obstacles. In this paper, we introduce a Sliding Mode Augmented by Reactive Transitioning (SMART) controller to detect the contact events, adjust the robot’s desired trajectory, and reject estimated disturbances in a goal reaching task. We employ a sliding mode controller to track the desired trajectory with a nonlinear disturbance observer (NDOB) to estimate the lumped disturbance, and a switching algorithm to adjust the desired robot trajectories. The proposed controller is validated on a pneumatic-driven fabric soft robot whose dynamics is described by a new extended rigid-arm model to fit the actuator design. A stability analysis of the proposed controller is also presented. Experimental results show that, despite modeling uncertainties, the robot can detect obstacles, adjust the reference trajectories to maintain compliance, and recover to track the original desired path once the obstacle is removed. Without force sensors, the proposed model-based controller can adjust the robot’s stiffness based on the estimated disturbance to achieve goal reaching and compliant interaction with unknown obstacles. 

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