ABSTRACT
Traditional robots are characterized by rigid structures, which restrict their range of motion and their application in environments where complex movements and safe human-robot interactions are required. Soft robots inspired by nature and characterized by soft compliant materials have emerged as an exciting alternative in unstructured environments. However, the use of multicomponent actuators with low power/weight ratios has prevented the development of truly bioinspired soft robots. Octopodes' limbs contain layers of muscular hydrostats, which provide them with a nearly limitless range of motions. In this work, we propose octopus-inspired muscular hydrostats powered by an emerging class of artificial muscles called twisted and coiled artificial muscles (TCAMs). TCAMs are fabricated by twisting and coiling inexpensive fibers, can sustain stresses up to 60 MPa, and provide tensile strokes of nearly 50% with <0.2 V/cm of input voltage. These artificial muscles overcome the limitations of other actuators in terms of cost, power, and portability. We developed four different configurations of muscular hydrostats with TCAMs arranged in different orientations to reproduce the main motions of octopodes' arms: shortening, torsion, bending, and extension. We also assembled an untethered waterproof device with on-board control, sensing, actuation, and a power source for driving our hydrostats underwater. The proposed TCAM-powered muscular hydrostats will pave the way for the development of compliant bioinspired robots that can be used to explore the underwater world and perform complex tasks in harsh and dangerous environments.
ABSTRACT
Based on the NASA in-Space Assembled Telescope (iSAT) study (Bulletin of the American Astronomical Society, 2019, 51, 50) which details the design and requirements for a 20-m parabolic in-space telescope, NASA Langley Research Center (LaRC) has been developing structural and robotic solutions to address the needs of building larger in-space assets. One of the structural methods studied involves stackable and collapsible modular solutions to address launch vehicle volume constraints. This solution uses a packing method that stacks struts in a dixie-cup like manner and a chemical composite bonding technique that reduces weight of the structure, adds strength, and offers the ability to de-bond the components for structural modifications. We present in this paper work towards a soft material robot end-effector, capable of suppling the manipulability, pressure, and temperature requirements for the bonding/de-bonding of these conical structural components. This work is done to investigate the feasibility of a hybrid soft robotic end-effector actuated by Twisted and Coiled Artificial Muscles (TCAMs) for in-space assembly tasks. TCAMs are a class of actuator which have garnered significant recent research interest due to their allowance for high force to weight ratio when compared to other popular methods of actuation within the field of soft robotics, and a muscle-tendon actuation design using TCAMs leads to a compact and lightweight system with controllable and tunable behavior. In addition to the muscle-tendon design, this paper also details the early investigation of an induction system for adhesive bonding/de-bonding and the sensors used for benchtop design and testing. Additionally, we discuss the viability of Robotic Operating System 2 (ROS2) and Gazebo modeling environments for soft robotics as they pertain to larger simulation efforts at LaRC. We show real world test results against simulation results for a method which divides the soft, continuous material of the end-effector into discrete links connected by spring-like joints.
ABSTRACT
This paper presents a method for the generation of trajectories for autonomous system operations. The proposed method is based on the use of Bernstein polynomial approximations to transcribe infinite dimensional optimization problems into nonlinear programming problems. These, in turn, can be solved using off-the-shelf optimization solvers. The main motivation for this approach is that Bernstein polynomials possess favorable geometric properties and yield computationally efficient algorithms that enable a trajectory planner to efficiently evaluate and enforce constraints along the vehicles' trajectories, including maximum speed and angular rates as well as minimum distance between trajectories and between the vehicles and obstacles. By virtue of these properties and algorithms, feasibility and safety constraints typically imposed on autonomous vehicle operations can be enforced and guaranteed independently of the order of the polynomials. To support the use of the proposed method we introduce BeBOT (Bernstein/Bézier Optimal Trajectories), an open-source toolbox that implements the operations and algorithms for Bernstein polynomials. We show that BeBOT can be used to efficiently generate feasible and collision-free trajectories for single and multiple vehicles, and can be deployed for real-time safety critical applications in complex environments.
