41 research outputs found
Estimation and Early Prediction of Grip Force Based on sEMG Signals and Deep Recurrent Neural Networks
Hands are used for communicating with the surrounding environment and have a
complex structure that enables them to perform various tasks with their
multiple degrees of freedom. Hand amputation can prevent a person from
performing their daily activities. In that event, finding a suitable, fast, and
reliable alternative for the missing limb can affect the lives of people who
suffer from such conditions. As the most important use of the hands is to grasp
objects, the purpose of this study is to accurately predict gripping force from
surface electromyography (sEMG) signals during a pinch-type grip. In that
regard, gripping force and sEMG signals are derived from 10 healthy subjects.
Results show that for this task, recurrent networks outperform nonrecurrent
ones, such as a fully connected multilayer perceptron (MLP) network. Gated
recurrent unit (GRU) and long short-term memory (LSTM) networks can predict the
gripping force with R-squared values of 0.994 and 0.992, respectively, and a
prediction rate of over 1300 predictions per second. The predominant advantage
of using such frameworks is that the gripping force can be predicted straight
from preprocessed sEMG signals without any form of feature extraction, not to
mention the ability to predict future force values using larger prediction
horizons adequately. The methods presented in this study can be used in the
myoelectric control of prosthetic hands or robotic grippers.Comment: 9 pages, accepted for publication in journal of the Brazilian Society
of Mechanical Sciences and Engineerin
A Reactive and Efficient Walking Pattern Generator for Robust Bipedal Locomotion
Available possibilities to prevent a biped robot from falling down in the
presence of severe disturbances are mainly Center of Pressure (CoP) modulation,
step location and timing adjustment, and angular momentum regulation. In this
paper, we aim at designing a walking pattern generator which employs an optimal
combination of these tools to generate robust gaits. In this approach, first,
the next step location and timing are decided consistent with the commanded
walking velocity and based on the Divergent Component of Motion (DCM)
measurement. This stage which is done by a very small-size Quadratic Program
(QP) uses the Linear Inverted Pendulum Model (LIPM) dynamics to adapt the
switching contact location and time. Then, consistent with the first stage, the
LIPM with flywheel dynamics is used to regenerate the DCM and angular momentum
trajectories at each control cycle. This is done by modulating the CoP and
Centroidal Momentum Pivot (CMP) to realize a desired DCM at the end of current
step. Simulation results show the merit of this reactive approach in generating
robust and dynamically consistent walking patterns
Robust Control of Flapping-Wing in Micro Aerial Vehicle to have a Smooth Flapping Motion
This paper in first sections, will give a brief overview of both the purpose and the challenges facing the actuator and structure of Micromechanical Flying Insects (MFIs) and, in the last sections, an appropriate controller will developed for flapping motion. A hierarchical architecture that divides the control unit into three main levels is introduced. This approach break a complex control problem into a multi-level set of smaller control schemes, each of which is responsible for a clearly defined task. Also, the controller at each level can be designed independently of those in other levels. A fourbar mechanism for the wing displacement amplification, and a new system for fourbar mechanism actuation (wing actuation) is developed. We will develop a flexible beam with piezoelectric actuators and sensor (called Smart Beam) that will used to excite the fourbar mechanism for flapping mode of flight. The Frequency Response Function (FRF) of the smart beam was obtained from a Finite Element (FE) model and experimental system identification. The corresponding transfer function was derived from the mu synthesis and several robust controllers were then designed to control the beam to reach a smooth flapping motion. Besides excitation of the fourbar mechanism, the Smart beam will be used to control of noise and disturbance in the structure of the wing system
Push Recovery of a Position-Controlled Humanoid Robot Based on Capture Point Feedback Control
In this paper, a combination of ankle and hip strategy is used for push
recovery of a position-controlled humanoid robot. Ankle strategy and hip
strategy are equivalent to Center of Pressure (CoP) and Centroidal Moment Pivot
(CMP) regulation respectively. For controlling the CMP and CoP we need a
torque-controlled robot, however most of the conventional humanoid robots are
position controlled. In this regard, we present an efficient way for
implementation of the hip and ankle strategies on a position controlled
humanoid robot. We employ a feedback controller to compensate the capture point
error. Using our scheme, a simple and practical push recovery controller is
designed which can be implemented on the most of the conventional humanoid
robots without the need for torque sensors. The effectiveness of the proposed
approach is verified through push recovery experiments on SURENA-Mini humanoid
robot under severe pushes
Optimization of Multi-zone Building HVAC Energy Consumption by Utilizing Fuzzy Model Based Predictive Controller
The rapid improvement of living standards has led to increased energy consumption in buildings worldwide. Globally, the energy consumed in buildings accounts for 20.1% of total delivered energy (EIA 2016). Improving energy efficiency in buildings therefore is an important component for combating climate change. This paper aims to improve end use energy efficiency in multi-zoned residential buildings through the application of thermal comfort based, energy optimization algorithms. We use a case study approach with a detailed analysis of a 4-story residential apartment building in central Illinois. The study building constitutes 21 thermal zones modeled in EnergyPlus. The model is validated using monthly energy consumption data. The effectiveness of four different steam heating system control methods are evaluated and described: a) a Model Predictive Controller (MPC) design based on neuro-fuzzy temperature predictor; b) a Proportional-Integral-Derivative (PID) tuned by fuzzy logic; c) a PID tuned by a genetic algorithm; and d) an on/off controller and the flow regulator based on indoor temperature. All are optimized for energy consumption reduction potential and thermal comfort. The main effect of the various control methods is tuning boiler feed flow by regulating the condensing cycle. A reduction in circulated steam flow results in decreased direct energy consumption and improved condensing pump efficiencies. We find that the MPC design using a neurofuzzy temperature predictor can reduce heating energy use by up to 38% in comparison with an on/off controller baseline
Online Bipedal Locomotion Adaptation for Stepping on Obstacles Using a Novel Foot Sensor
In this paper, we present a novel control architecture for the online
adaptation of bipedal locomotion on inclined obstacles. In particular, we
introduce a novel, cost-effective, and versatile foot sensor to detect the
proximity of the robot's feet to the ground (bump sensor). By employing this
sensor, feedback controllers are implemented to reduce the impact forces during
the transition of the swing to stance phase or steeping on inclined unseen
obstacles. Compared to conventional sensors based on contact reaction force,
this sensor detects the distance to the ground or obstacles before the foot
touches the obstacle and therefore provides predictive information to
anticipate the obstacles. The controller of the proposed bump sensor interacts
with another admittance controller to adjust leg length. The walking
experiments show successful locomotion on the unseen inclined obstacle without
reducing the locomotion speed with a slope angle of 12. Foot position error
causes a hard impact with the ground as a consequence of accumulative error
caused by links and connections' deflection (which is manufactured by
university tools). The proposed framework drastically reduces the feet' impact
with the ground.Comment: 6 pages, 2022 IEEE-RAS 21th International Conference on Humanoid
Robots (Humanoids
A Global Parameter-Based Wave Absorbing Controller for Smart Structures: Theory and Experiment
NRC publication: Ye