5 research outputs found
Optimizing Lead Time in Fall Detection for a Planar Bipedal Robot
For legged robots to operate in complex terrains, they must be robust to the
disturbances and uncertainties they encounter. This paper contributes to
enhancing robustness through the design of fall detection/prediction algorithms
that will provide sufficient lead time for corrective motions to be taken.
Falls can be caused by abrupt (fast-acting), incipient (slow-acting), or
intermittent (non-continuous) faults. Early fall detection is a challenging
task due to the masking effects of controllers (through their disturbance
attenuation actions), the inverse relationship between lead time and false
positive rates, and the temporal behavior of the faults/underlying factors. In
this paper, we propose a fall detection algorithm that is capable of detecting
both incipient and abrupt faults while maximizing lead time and meeting desired
thresholds on the false positive and negative rates
Fall Prediction for Bipedal Robots: The Standing Phase
This paper presents a novel approach to fall prediction for bipedal robots,
specifically targeting the detection of potential falls while standing caused
by abrupt, incipient, and intermittent faults. Leveraging a 1D convolutional
neural network (CNN), our method aims to maximize lead time for fall prediction
while minimizing false positive rates. The proposed algorithm uniquely
integrates the detection of various fault types and estimates the lead time for
potential falls. Our contributions include the development of an algorithm
capable of detecting abrupt, incipient, and intermittent faults in full-sized
robots, its implementation using both simulation and hardware data for a
humanoid robot, and a method for estimating lead time. Evaluation metrics,
including false positive rate, lead time, and response time, demonstrate the
efficacy of our approach. Particularly, our model achieves impressive lead
times and response times across different fault scenarios with a false positive
rate of 0. The findings of this study hold significant implications for
enhancing the safety and reliability of bipedal robotic systems.Comment: Submitted to ICRA 2024. This work has been submitted to the IEEE for
possible publication. Copyright may be transferred without notice, after
which this version may no longer be accessibl
Feedback Control of an Exoskeleton for Paraplegics: Toward Robustly Stable Hands-free Dynamic Walking
This manuscript presents control of a high-DOF fully actuated lower-limb
exoskeleton for paraplegic individuals. The key novelty is the ability for the
user to walk without the use of crutches or other external means of
stabilization. We harness the power of modern optimization techniques and
supervised machine learning to develop a smooth feedback control policy that
provides robust velocity regulation and perturbation rejection. Preliminary
evaluation of the stability and robustness of the proposed approach is
demonstrated through the Gazebo simulation environment. In addition,
preliminary experimental results with (complete) paraplegic individuals are
included for the previous version of the controller.Comment: Submitted to IEEE Control System Magazine. This version addresses
reviewers' concerns about the robustness of the algorithm and the motivation
for using such exoskeleton
Feedback Control of an Exoskeleton for Paraplegics: Toward Robustly Stable, Hands-Free Dynamic Walking
"I will never forget the emotion of my first steps […]," were the words of Fran?oise, the first user during initial trials of the exoskeleton ATALANTE [1]. "I am tall again!" were the words of Sandy (the fourth user) after standing up in the exoskeleton. During these early tests, complete paraplegic patients dynamically walked up to 10 m without crutches or other assistance using a feedback control method originally invented for bipedal robots. As discussed in "Summary," this article describes the hardware (shown in Figure 1) that was designed to achieve hands-free dynamic walking, the control laws that were deployed (and those being developed) to provide enhanced mobility and robustness, and preliminary test results. In this article, dynamic walking refers to a motion that is orbitally stable as opposed to statically stable