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1. An untethered isoperimetric soft robot

   https://doi.org/10.1126/scirobotics.aaz0492  

   Usevitch, Nathan S. ; Hammond, Zachary M. ; Schwager, Mac ; Okamura, Allison M. ; Hawkes, Elliot W. ; Follmer, Sean ( March 2020 , Science Robotics)

   For robots to be useful for real-world applications, they must be safe around humans, be adaptable to their environment, and operate in an untethered manner. Soft robots could potentially meet these requirements; however, existing soft robotic architectures are limited by their ability to scale to human sizes and operate at these scales without a tether to transmit power or pressurized air from an external source. Here, we report an untethered, inflated robotic truss, composed of thin-walled inflatable tubes, capable of shape change by continuously relocating its joints, while its total edge length remains constant. Specifically, a set of identical roller modules each pinch the tube to create an effective joint that separates two edges, and modules can be connected to form complex structures. Driving a roller module along a tube changes the overall shape, lengthening one edge and shortening another, while the total edge length and hence fluid volume remain constant. This isoperimetric behavior allows the robot to operate without compressing air or requiring a tether. Our concept brings together advantages from three distinct types of robots—soft, collective, and truss-based—while overcoming certain limitations of each. Our robots are robust and safe, like soft robots, but not limited by a tether;more »are modular, like collective robots, but not limited by complex subunits; and are shape-changing, like truss robots, but not limited by rigid linear actuators. We demonstrate two-dimensional (2D) robots capable of shape change and a human-scale 3D robot capable of punctuated rolling locomotion and manipulation, all constructed with the same modular rollers and operating without a tether.« less
2. Kinematics and Stiffness Modeling of Soft Robot With a Concentric Backbone

   https://doi.org/10.1115/1.4055860  

   Xiao, Qingyu ; Musa, Mishek ; Godage, Isuru S. ; Su, Hao ; Chen, Yue ( October 2023 , Journal of Mechanisms and Robotics)

   Abstract Soft robots can undergo large elastic deformations and adapt to complex shapes. However, they lack the structural strength to withstand external loads due to the intrinsic compliance of fabrication materials (silicone or rubber). In this paper, we present a novel stiffness modulation approach that controls the robot’s stiffness on-demand without permanently affecting the intrinsic compliance of the elastomeric body. Inspired by concentric tube robots, this approach uses a Nitinol tube as the backbone, which can be slid in and out of the soft robot body to achieve robot pose or stiffness modulation. To validate the proposed idea, we fabricated a tendon-driven concentric tube (TDCT) soft robot and developed the model based on Cosserat rod theory. The model is validated in different scenarios by varying the joint-space tendon input and task-space external contact force. Experimental results indicate that the model is capable of estimating the shape of the TDCT soft robot with an average root-mean-square error (RMSE) of 0.90 (0.56% of total length) mm and average tip error of 1.49 (0.93% of total length) mm. Simulation studies demonstrate that the Nitinol backbone insertion can enhance the kinematic workspace and reduce the compliance of the TDCT soft robot by 57.7%. Twomore »case studies (object manipulation and soft laparoscopic photodynamic therapy) are presented to demonstrate the potential application of the proposed design.« less
3. A perspective on the neuromorphic control of legged locomotion in past, present, and future insect-like robots

   https://doi.org/10.1088/2634-4386/acc04f  

   Szczecinski, Nicholas Stephen ; Goldsmith, Clarissa ; Nourse, William ; Quinn, Roger D. ( March 2023 , Neuromorphic Computing and Engineering)

   This article is a historical perspective on how the study of the neuromechanics of insects and other arthropods has inspired the construction, and especially the control, of hexapod robots. Many hexapod robots’ control systems share common features, including: 1. Direction of motor output of each joint (i.e., to flex or extend) in the leg is gated by an oscillatory or bistable gating mechanism; 2. The phasing between each joint is influenced by proprioceptive feedback from the periphery (e.g., joint angles, leg load) or central connections between joint controllers; and 3. Behavior can be directed (e.g., walking along a curved path) via low-dimensional, broadly-acting descending inputs to the network. These distributed control schemes are inspired by, and in some robots, closely mimic the organization of the nervous systems of insects, the natural hexapods, as well as crustaceans. Nearly a century of research has revealed organizational principles such as central pattern generators (CPGs), the role of proprioceptive feedback in control, and command neurons. These concepts have inspired the control systems of hexapod robots in the past, in which these structures were applied to robot controllers with neuromorphic (i.e., distributed) organization, but not neuromorphic computational units (i.e., neurons) or computational hardware (i.e., hardware-accelerated neurons). Presently, several hexapodmore »robots are controlled with neuromorphic computational units with or without neuromorphic organization, almost always without neuromorphic hardware. In the near future, we expect to see hexapod robots whose controllers include neuromorphic organization, computational units, and hardware. Such robots may exhibit the full mobility of their insect counterparts thanks to a “biology-first” approach to controller design. This perspective is not a comprehensive review of the neuroscientific literature but is meant to give a gentle introduction into the principles that underlie models and inspire neuromorphic robot controllers. Deeper reviews of particular topics from biology are suggested throughout.

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4. Tractable and Intuitive Dynamic Model for Soft Robots via the Recursive Newton-Euler Algorithm

   https://doi.org/10.1109/RoboSoft54090.2022.9762215  

   Jensen, Spencer W. ; Johnson, Curtis C. ; Lindberg, Alexa M. ; Killpack, Marc D. ( April 2022 , IEEE International Conference on Soft Robotics (RoboSoft))

   Because of the complex nature of soft robots, formulating dynamic models that are simple, efficient, and sufficiently accurate for simulation or control is a difficult task. This paper introduces an algorithm based on a recursive Newton-Euler (RNE) approach that enables an accurate and tractable lumped parameter dynamic model. This model scales linearly in computational complexity with the number of discrete segments. We validate this model by comparing it to actual hardware data from a three-joint continuum soft robot (with six degrees of freedom represented in a constant curvature kinematic model). The results show that this RNE-based model can be computed faster than real-time. We also show that with minimal system identification, a simulation performed using the dynamic model matches the real robot data with a median error of 3.15 degrees.
5. WSR: A WiFi Sensor for Collaborative Robotics

   Ninad Jadhav, Weiying Wang ( June 2021 , ArXivorg)

   In this paper we derive a new capability for robots to measure relative direction, or Angle-of-Arrival (AOA), to other robots, while operating in non-line-of-sight and unmapped environments, without requiring external infrastructure. We do so by capturing all of the paths that a WiFi signal traverses as it travels from a transmitting to a receiving robot in the team, which we term as an AOA profile. The key intuition behind our approach is to emulate antenna arrays in the air as a robot moves freely in 2D or 3D space. The small differences in the phase and amplitude of WiFi signals are thus processed with knowledge of a robots’ local displacements (often provided via inertial sensors) to obtain the profile, via a method akin to Synthetic Aperture Radar (SAR). The main contribution of this work is the development of i) a framework to accommodate arbitrary 2D and 3D trajectories, as well as continuous mobility of both transmitting and receiving robots, while computing AOA profiles between them and ii) an accompanying analysis that provides a lower bound on variance of AOA estimation as a function of robot trajectory geometry that is based on the Cramer Rao Bound and antenna array theory. Thismore »is a critical distinction with previous work on SAR that restricts robot mobility to prescribed motion patterns, does not generalize to the full 3D space, and/or requires transmitting robots to be static during data acquisition periods. In fact, we find that allowing robots to use their full mobility in 3D space while performing SAR, results in more accurate AOA profiles and thus better AOA estimation. We formally characterize this observation as the informativeness of the trajectory; a computable quantity for which we derive a closed form. All theoretical developments are substantiated by extensive simulation and hardware experiments on air/ground robot platforms. Our experimental results bolster our theoretical findings, demonstrating that 3D trajectories provide enhanced and consistent accuracy, with AOA error of less than 10 deg for 95% of trials. We also show that our formulation can be used with an off-the-shelf trajectory estimation sensor (Intel RealSense T265 tracking camera), for estimating the robots’ local displacements, and we provide theoretical as well as empirical results that show the impact of typical trajectory estimation errors on the measured AOA. Finally, we demonstrate the performance of our system on a multi-robot task where a heterogeneous air/ground pair of robots continuously measure AOA profiles over a WiFi link to achieve dynamic rendezvous in an unmapped, 300 square meter environment with occlusions.« less