Dynamics for variable length multisection continuum arms

Variable length multisection continuum arms are a class of continuum robotic manipulators that generate motion by structural mechanical deformation. Unlike most continuum robots, the sections of these arms do not have (central) supporting flexible backbone, and are actuated by multiple variable length actuators. Because of the constraining nature of actuators, the continuum sections can bend and/or elongate (compress) depending on the elongation/contraction characteristics of the actuators being used. Continuum arms have a number of distinctive differences with respect to traditional rigid arms namely: smooth bending, high inherent compliance, and adaptive whole arm grasping. However, due to numerical instability and the complexity of curve parametric models, there are no spatial dynamic models for multisection continuum arms. This paper introduces novel spatial dynamics and applies these to variable length multisection continuum arms with any number of sections. An efficient recursive computational scheme for deriving the equations of motion is presented. This is applied in a general form based on structurally accurate and numerically well-posed modal kinematics that assumes circular arc deformation of continuum sections without torsion. It is shown that the proposed modal dynamics are highly scalable, producing efficient and accurate numerical results. The spatial dynamic simulation results are experimentally validated using a pneumatic muscle actuated multisection prototype continuum arm. For the first time this enables investigation of spatial dynamic effects in this class of continuum arms

A Lumped-Mass Model for Large Deformation Continuum Surfaces Actuated by Continuum Robotic Arms

Currently, flexible surfaces enabled to be actuated by robotic arms are experiencing high interest and demand for robotic applications in various areas such as healthcare, automotive , aerospace, and manufacturing. However, their design and control thus far has largely been based on "trial and error" methods requiring multiple trials and/or high levels of user specialization. Robust methods to realize flexible surfaces with the ability to deform into large curvatures therefore require a reliable, validated model that takes into account many physical and mechanical properties including elasticity, material characteristics, gravity, external forces, and thickness shear effects. The derivation of such a model would then enable the further development of predictive-based control methods for flexible robotic surfaces. This paper presents a lumped-mass model for flexible surfaces undergoing large deformation due to actuation by continuum robotic arms. The resulting model includes mechanical and physical properties for both the surface and actuation elements to predict deformation in multiple curvature directions and actuation configurations. The model is validated against an experimental system where measured displacements between the experimental and modeling results showed considerable agreement with a mean error magnitude of about 1% of the length of the surface at the final deformed shapes

Model Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges

Continuum soft robots are mechanical systems entirely made of continuously deformable elements. This design solution aims to bring robots closer to invertebrate animals and soft appendices of vertebrate animals (e.g., an elephant's trunk, a monkey's tail). This work aims to introduce the control theorist perspective to this novel development in robotics. We aim to remove the barriers to entry into this field by presenting existing results and future challenges using a unified language and within a coherent framework. Indeed, the main difficulty in entering this field is the wide variability of terminology and scientific backgrounds, making it quite hard to acquire a comprehensive view on the topic. Another limiting factor is that it is not obvious where to draw a clear line between the limitations imposed by the technology not being mature yet and the challenges intrinsic to this class of robots. In this work, we argue that the intrinsic effects are the continuum or multi-body dynamics, the presence of a non-negligible elastic potential field, and the variability in sensing and actuation strategies.Comment: 69 pages, 13 figure

Continuum Robots for Space Applications Based on Layer-Jamming Scales with Stiffness Capability

Continuum robots, which have continuous mechanical structures comparable to the flexibility in elephant trunks and octopus arms, have been primarily geared toward the medical and defense communities. In space, however, NASA projects these robots to have a place in irregular inspection routines. The inherent compliance and bending of these continuum arms are especially suitable for inspection in obstructed spaces to ensure proper equipment functionality. In this paper, we propose a new solution that improves on the functionality of previous continuum robots, via a novel mechanical scaly layer-jamming design. Layer-jamming assisted continuum arms have previously required pneumatic sources for actuation, which limit their portability and usage in aerospace applications. This paper combines the compliance of continuum arms and stiffness modulation of the layer jamming mechanism to design new hybrid layer jamming continuum arms. The novel designs use an electromechanical actuation which eliminates the previous need for pneumatic actuation therefore making the hardware compact and portable

Dynamic Environmental Monitoring using Intelligent Tendril Robots

Traditional robots are constructed from rigid links which facilitate both stiffness and accuracy. However, these systems operate best in open, highly structured spaces, and environments traversable by this technology are inherently restricted to scales and geometries which match the size and shape of the links. Conversely, continuous backbone continuum robots have enormous potential for adaptive exploration of unstructured environments. However, to date there has been very little research on algorithms for learning and adapting to changes in environmental conditions with continuum robots. In this research, we introduce new results in learning policies for novel long, thin, continuously bending continuum tendril robots aimed toward applications such as remote inspection and sensor mobility for improved sample acquisition. The results could also have potential applica tions in defense and security, search and rescue in hazardous environmental conditions, and as an innovative option for sensor placement in environmental monitoring. Using a prototype continuum tendril robot previously developed at Clemson University, we demonstrate the new learning policy for the tendrils adaptive sensor placement and remote inspection within an environment seeded with numerous disparate and slowly (over a matter of hours) time-varying sources, and discuss the potential for use of such robot tendrils in environmental monitoring applications. The learning algorithm implemented in real-time is shown to help the tendril to adapt its sensor placement to changing environmental sources