30 research outputs found
The Effect of Tail Stiffness on a Sprawling Quadruped Locomotion
A distinctive feature of quadrupeds that is integral to their locomotion is
the tail. Tails serve many purposes in biological systems including propulsion,
counterbalance, and stabilization while walking, running, climbing, or jumping.
Similarly, tails in legged robots may augment the stability and maneuverability
of legged robots by providing an additional point of contact with the ground.
However, in the field of terrestrial bio-inspired legged robotics, the tail is
often ignored because of the difficulties in design and control. This study
will test the hypothesis that a variable stiffness robotic tail can improve the
performance of a sprawling quadruped robot by enhancing its stability and
maneuverability in various environments. To test our hypothesis, we add a
multi-segment, cable-driven, flexible tail, whose stiffness is controlled by a
single servo motor in conjunction with a reel and cable system, to the
underactuated sprawling quadruped robot. By controlling the stiffness of the
tail, we have shown that the stability of locomotion on rough terrain and the
climbing ability of the robot are improved compared to the movement with a
rigid tail and no tail. The flexible tail design also provides passively
controlled tail undulation capabilities through the robot's lateral movement,
which contributes to stability
Locomotion and Obstacle Avoidance of a Worm-like Soft Robot
This paper presents a soft earthworm robot that is capable of both efficient
locomotion and obstacle avoidance. The robot is designed to replicate the
unique locomotion mechanisms of earthworms, which enable them to move through
narrow and complex environments with ease. The robot consists of multiple
segments, each with its own set of actuators, that are connected through rigid
plastic joints, allowing for increased adaptability and flexibility in
navigating different environments. The robot utilizes proprioceptive sensing
and control algorithms to detect and avoid obstacles in real-time while
maintaining efficient locomotion. The robot uses a pneumatic actuation system
to mimic the circumnutation behavior exhibited by plant roots in order to
navigate through complex environments. The results demonstrate the capabilities
of the robot for navigating through cluttered environments, making this
development significant for various fields of robotics, including search and
rescue, environmental monitoring, and medical procedures
The Effect of Flagella Stiffness on the Locomotion of a Multi-Flagellated Robot at Low Reynolds Environment
Microorganisms such as algae and bacteria move in a viscous environment with
extremely low Reynolds (), where the viscous drag dominates the inertial
forces. They have adapted to this environment by developing specialized
features such as whole-body deformations and flexible structures such as
flagella (with various shapes, sizes, and numbers) that break the symmetry
during the motion. In this study, we hypothesize that the changes in the
flexibility of the flagella during a cycle of movement impact locomotion
dynamics of flagellated locomotion. To test our hypothesis, we developed an
autonomous, self-propelled robot with four flexible, multi-segmented flagella
actuated together by a single DC motor. The stiffness of the flagella during
the locomotion is controlled via a cable-driven mechanism attached to the
center of the robot. Experimental assessments of the robot's swimming
demonstrate that increasing the flexibility of the flagella during recovery
stroke and reducing the flexibility during power stroke improves the swimming
performance of the robot. Our results give insight into how these
microorganisms manipulate their biological features to propel themselves in low
viscous media and are of great interest to biomedical and research
applications
Soft Wrist Exosuit Actuated by Fabric Pneumatic Artificial Muscles
Recently, soft actuator-based exosuits have gained interest, due to their
high strength-to-weight ratio, inherent safety, and low cost. We present a
novel wrist exosuit actuated by fabric pneumatic artificial muscles that can
move the wrist in flexion/extension and ulnar/radial deviation. We derive a
model representing the torque exerted by the exosuit and introduce a
model-based optimization methodology for the selection of placement parameters
of the exosuit muscles. We evaluate the accuracy of the model by measuring the
exosuit torques throughout the full range of wrist flexion/extension. When
accounting for the displacement of the mounting points, the model predicts the
exosuit torque with a mean absolute error of 0.279 Nm, which is 26.1% of the
average measured torque. To explore the capabilities of the exosuit to move the
human body, we measure its range of motion on a passive human wrist; the
exosuit is able to achieve 55.0% of the active biological range in flexion,
69.1% in extension, 68.6% in ulnar deviation, and 68.4% in radial deviation.
Finally, we demonstrate the device controlling the passive human wrist to move
to a desired orientation in the flexion/extension plane and along a
two-degree-of-freedom trajectory.Comment: 16 pages, 15 figure
Stable Real-Time Feedback Control of a Pneumatic Soft Robot
Soft actuators offer compliant and safe interaction with an unstructured
environment compared to their rigid counterparts. However, control of these
systems is often challenging because they are inherently under-actuated, have
infinite degrees of freedom (DoF), and their mechanical properties can change
by unknown external loads. Existing works mainly relied on discretization and
reduction, suffering from either low accuracy or high computational cost for
real-time control purposes. Recently, we presented an infinite-dimensional
feedback controller for soft manipulators modeled by partial differential
equations (PDEs) based on the Cosserat rod theory. In this study, we examine
how to implement this controller in real-time using only a limited number of
actuators. To do so, we formulate a convex quadratic programming problem that
tunes the feedback gains of the controller in real time such that it becomes
realizable by the actuators. We evaluated the controller's performance through
experiments on a physical soft robot capable of planar motions and show that
the actual controller implemented by the finite-dimensional actuators still
preserves the stabilizing property of the desired infinite-dimensional
controller. This research fills the gap between the infinite-dimensional
control design and finite-dimensional actuation in practice and suggests a
promising direction for exploring PDE-based control design for soft robots
Machine Learning-Driven Burrowing with a Snake-Like Robot
Subterranean burrowing is inherently difficult for robots because of the high
forces experienced as well as the high amount of uncertainty in this domain.
Because of the difficulty in modeling forces in granular media, we propose the
use of a novel machine-learning control strategy to obtain optimal techniques
for vertical self-burrowing. In this paper, we realize a snake-like
bio-inspired robot that is equipped with an IMU and two triple-axis
magnetometers. Utilizing magnetic field strength as an analog for depth, a
novel deep learning architecture was proposed based on sinusoidal and random
data in order to obtain a more efficient strategy for vertical self-burrowing.
This strategy was able to outperform many other standard burrowing techniques
and was able to automatically reach targeted burrowing depths. We hope these
results will serve as a proof of concept for how optimization can be used to
unlock the secrets of navigating in the subterranean world more efficiently
Design of Soft, Modular Appendages for a Bio-inspired Multi-Legged Terrestrial Robot
Soft robots have the ability to adapt to their environment, which makes them
suitable for use in disaster areas and agricultural fields, where their
mobility is constrained by complex terrain. One of the main challenges in
developing soft terrestrial robots is that the robot must be soft enough to
adapt to its environment, but also rigid enough to exert the required force on
the ground to locomote. In this paper, we report a pneumatically driven, soft
modular appendage made of silicone for a terrestrial robot capable of
generating specific mechanical movement to locomote and transport loads in the
desired direction. This two-segmented soft appendage uses actuation in between
the joint and the lower segment of the appendage to ensure adequate rigidity to
exert the required force to locomote. A prototype of a soft-rigid-bodied
tethered physical robot was developed and two sets of experiments were carried
out in both air and underwater environments to assess its performance. The
experimental results address the effectiveness of the soft appendage to
generate adequate force to navigate through various environments and our design
method offers a simple, low-cost, and efficient way to develop terradynamically
capable soft appendages that can be used in a variety of locomotion
applications
The effect of tail stiffness on a sprawling quadruped locomotion
A distinctive feature of quadrupeds that is integral to their locomotion is the tail. Tails serve many purposes in biological systems, including propulsion, counterbalance, and stabilization while walking, running, climbing, or jumping. Similarly, tails in legged robots may augment the stability and maneuverability of legged robots by providing an additional point of contact with the ground. However, in the field of terrestrial bio-inspired legged robotics, the tail is often ignored because of the difficulties in design and control. In this study, we test the hypothesis that a variable stiffness robotic tail can improve the performance of a sprawling quadruped robot by enhancing its stability and maneuverability in various environments. In order to validate our hypothesis, we integrated a cable-driven, flexible tail with multiple segments into the underactuated sprawling quadruped robot, where a single servo motor working alongside a reel and cable mechanism regulates the tail’s stiffness. Our results demonstrated that by controlling the stiffness of the tail, the stability of locomotion on rough terrain and the climbing ability of the robot are improved compared to the movement with a rigid tail and no tail. Our findings highlight that constant ground support provided by the flexible tail is key to maintaining stable locomotion. This ensured a predictable gait cycle, eliminating unexpected turning and slipping, resulting in an increase in locomotion speed and efficiency. Additionally, we observed the robot’s enhanced climbing ability on surfaces inclined up to 20°. The flexibility of the tail enabled the robot to overcome obstacles without external sensing, exhibiting significant adaptability across various terrains