scholarly journals Multisensory Influences on Driver Steering During Curve Navigation

2018 ◽  
Vol 61 (2) ◽  
pp. 337-347
Author(s):  
Kristen L. Macuga
Keyword(s):  
Visual Information ◽  
Visual Cues ◽  
Closed Loop ◽  
Critical Role ◽  
Open Loop ◽  
Steering Wheel ◽  
Steering Control ◽  
Multiple Sources ◽  
Somatosensory Information ◽  
Inertial Cues

Objective: The effects of inertial (vestibular and somatosensory) information on driver steering during curve navigation were investigated, using an electric four-wheel mobility vehicle outfitted with a steering wheel and a portable virtual reality system. Background: When driving, multiple sources of perceptual information are available. Researchers have focused on visual information, which plays a critical role in steering control. However, it is not yet well established how inertial information might contribute. Methods: I biased inertial cues by varying visual/inertial gains (doubled, halved, reversed), as drivers negotiated curving paths, and measured steering accuracy and efficiency. I also assessed whether being exposed to inertial biases had an impact on postbias steering by comparing pre- and posttest session performance measures. Results: Doubling or halving inertial cues had little effect on steering performance. Inertial information only disrupted steering when it was reversed with respect to visual information. Over time, the influence of this extreme inertial bias was reduced though not eliminated. Postbias curve navigation performance was not impacted, likely because participants had learned to disregard, rather than integrate, biased inertial cues. Conclusion: Results suggest that biased inertial information has little influence on curve navigation performance when visual information is available. Application: Though inertial cues may be important for open-loop steering, when visual cues are unavailable, their role in closed-loop steering seems less influential. This has implications for driving simulation and suggests that inertial discrepancies due to limitations in motion-cuing capabilities may not be all that problematic for the simulation of closed-loop curve steering tasks.

HAND–EYE COORDINATION THROUGH ENDPOINT CLOSED-LOOP AND LEARNED ENDPOINT OPEN-LOOP VISUAL SERVO CONTROL

2005 ◽  
Vol 02 (02) ◽  
pp. 203-224 ◽  
Author(s):  
CHRIS GASKETT ◽  
ALEŠ UDE ◽  
GORDON CHENG
Keyword(s):  
Visual Cues ◽  
Closed Loop ◽  
Open Loop ◽  
Servo Control ◽  
Visual Servo ◽  
Visual Servo Control ◽  
Motor Mapping ◽  
Hand Eye Coordination ◽  
Coordination System ◽  
Bimanual Reaching

We propose a hand-eye coordination system for a humanoid robot that supports bimanual reaching. The system combines endpoint closed-loop and open-loop visual servo control. The closed-loop component moves the eyes, head, arms, and torso, based on the position of the target and the robot's hands, as seen by the robot's head-mounted cameras. The open-loop component uses a motor-motor mapping that is learnt online to support movement when visual cues are not available.

scholarly journals Optimal closed-loop wake steering, Part 2: Diurnal cycle atmospheric boundary layer conditions

2021 ◽  
Author(s):  
Michael F. Howland ◽  
Aditya S. Ghate ◽  
Jesus Bas Quesada ◽  
Juan Jose Pena Martinez ◽  
Wei Zhong ◽  
...  
Keyword(s):  
Diurnal Cycle ◽  
Wind Direction ◽  
Energy Production ◽  
Wind Farm ◽  
Closed Loop ◽  
Atmospheric Stability ◽  
Open Loop ◽  
Lookup Table ◽  
Steering Control ◽  
Set Point

Abstract. The magnitude of wake interactions between individual wind turbines depends on the atmospheric stability. We investigate strategies for wake loss mitigation through the use of closed-loop wake steering using large eddy simulations of the diurnal cycle, where variations in the surface heat flux in time modify the atmospheric stability, wind speed and direction, shear, turbulence, and other atmospheric boundary layer flow (ABL) features. The closed-loop wake steering control methodology developed in Part 1 (Howland et al., Wind Energy Science, 2020, 5, 1315–1338) is implemented in an eight turbine wind farm in large eddy simulations of the diurnal cycle. The optimal yaw misalignment set-points depend on the wind direction, which varies in time during the diurnal cycle. To improve the application of wake steering control in transient ABL conditions with an evolving mean flow state, we develop a regression-based wind direction forecast method. We compare the closed-loop wake steering control methodology to baseline yaw aligned control and open-loop lookup table control for various selections of the yaw misalignment set-point update frequency, which dictates the balance between wind direction tracking and yaw activity. Closed-loop wake steering with set-point optimization under uncertainty results in higher collective energy production than both baseline yaw aligned control and open-loop lookup table control. The increase in wind farm energy production for closed- and open-loop wake steering control compared to baseline yaw aligned control, is 4.0–4.1 % and 3.4–3.8 %, respectively, with the range indicating variations in the energy increase results depending on the set-point update frequency. The primary energy increases through wake steering occur during stable ABL conditions. Open-loop lookup table control decreases energy production in the convective ABL conditions simulated, compared to baseline yaw aligned control, while closed-loop control increases energy production in convective conditions.

On closed-loop equilibrium strategies for mean-field stochastic linear quadratic problems

2020 ◽  
Vol 26 ◽  
pp. 41
Author(s):  
Tianxiao Wang
Keyword(s):  
Optimal Control ◽  
Closed Loop ◽  
Optimal Control Problems ◽  
Mean Field ◽  
Open Loop ◽  
Time Inconsistency ◽  
Control Problems ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Equilibrium Strategies

This article is concerned with linear quadratic optimal control problems of mean-field stochastic differential equations (MF-SDE) with deterministic coefficients. To treat the time inconsistency of the optimal control problems, linear closed-loop equilibrium strategies are introduced and characterized by variational approach. Our developed methodology drops the delicate convergence procedures in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. When the MF-SDE reduces to SDE, our Riccati system coincides with the analogue in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. However, these two systems are in general different from each other due to the conditional mean-field terms in the MF-SDE. Eventually, the comparisons with pre-committed optimal strategies, open-loop equilibrium strategies are given in details.

Comparison of Dc-Dc SEPIC, CUK and Flyback Converters Based LED Drivers

2020 ◽  
pp. 99-107
Author(s):  
Erdal Sehirli
Keyword(s):  
Integrated Circuit ◽  
Closed Loop ◽  
Input Voltage ◽  
Open Loop ◽  
Current Sensor ◽  
Switching Frequency ◽  
Led Driver ◽  
Advantages And Disadvantages ◽  
Led Drivers ◽  
Conduction Mode

This paper presents the comparison of LED driver topologies that include SEPIC, CUK and FLYBACK DC-DC converters. Both topologies are designed for 8W power and operated in discontinuous conduction mode (DCM) with 88 kHz switching frequency. Furthermore, inductors of SEPIC and CUK converters are wounded as coupled. Applications are realized by using SG3524 integrated circuit for open loop and PIC16F877 microcontroller for closed loop. Besides, ACS712 current sensor used to limit maximum LED current for closed loop applications. Finally, SEPIC, CUK and FLYBACK DC-DC LED drivers are compared with respect to LED current, LED voltage, input voltage and current. Also, advantages and disadvantages of all topologies are concluded.

scholarly journals Parallel Point Clouds: Hybrid Point Cloud Generation and 3D Model Enhancement via Virtual–Real Integration

2021 ◽  
Vol 13 (15) ◽  
pp. 2868
Author(s):  
Yonglin Tian ◽  
Xiao Wang ◽  
Yu Shen ◽  
Zhongzheng Guo ◽  
Zilei Wang ◽  
...  
Keyword(s):  
Point Cloud ◽  
Closed Loop ◽  
Real Data ◽  
Point Clouds ◽  
Autonomous Driving ◽  
Training Model ◽  
Labor Cost ◽  
Open Loop ◽  
Training Dataset ◽  
Data Annotation

Three-dimensional information perception from point clouds is of vital importance for improving the ability of machines to understand the world, especially for autonomous driving and unmanned aerial vehicles. Data annotation for point clouds is one of the most challenging and costly tasks. In this paper, we propose a closed-loop and virtual–real interactive point cloud generation and model-upgrading framework called Parallel Point Clouds (PPCs). To our best knowledge, this is the first time that the training model has been changed from an open-loop to a closed-loop mechanism. The feedback from the evaluation results is used to update the training dataset, benefiting from the flexibility of artificial scenes. Under the framework, a point-based LiDAR simulation model is proposed, which greatly simplifies the scanning operation. Besides, a group-based placing method is put forward to integrate hybrid point clouds, via locating candidate positions for virtual objects in real scenes. Taking advantage of the CAD models and mobile LiDAR devices, two hybrid point cloud datasets, i.e., ShapeKITTI and MobilePointClouds, are built for 3D detection tasks. With almost zero labor cost on data annotation for newly added objects, the models (PointPillars) trained with ShapeKITTI and MobilePointClouds achieved 78.6% and 60.0% of the average precision of the model trained with real data on 3D detection, respectively.

scholarly journals The processing of visual food cues during bitter aftertaste perception in females with high vs. low disgust propensity: an fMRI study

2021 ◽  
Author(s):  
Anne Schienle ◽  
Albert Wabnegger
Keyword(s):  
Personality Trait ◽  
Visual Cues ◽  
Critical Role ◽  
Relevant Information ◽  
Anterior Cingulate ◽  
Conflict Monitoring ◽  
Food Cues ◽  
Sweet Food ◽  
Visual Food Cues ◽  
Disgust Propensity

AbstractAn extremely bitter taste can signal food spoilage, and therefore typically elicits disgust. The present cross-modal functional magnetic resonance imaging experiment investigated whether the personality trait ‘disgust propensity’ (DP; temporally stable tendency to experience disgust across different situations) has an influence on the processing of visual food cues during bitter aftertaste perception. Thirty females with high DP and 30 females with low DP viewed images depicting sweet food (e.g., cakes, ice cream) and vegetables, once in combination with an extremely bitter aftertaste (concentrated wormwood tea), and once with a neutral taste (water). Females highly prone to disgust (compared to low disgust-prone females) showed increased activity in the anterior cingulate cortex (ACC) and increased mPFC-insula connectivity when presented with the mismatch of a bitter aftertaste and visual cues of sweet food. The ACC is involved in conflict monitoring and is strongly interconnected with insular areas. This connection plays a critical role in awareness of changes in homeostatic states. Our findings indicate that the personality trait DP is associated with cross-modal integration processes of disgust-relevant information. Females high in DP were more alert to food-related sensory mismatch (pleasant visual features, aversive taste) than females low in DP.

scholarly journals Converting MST to TSP Path by Branch Elimination

2020 ◽  
Vol 11 (1) ◽  
pp. 177
Author(s):  
Pasi Fränti ◽  
Teemu Nenonen ◽  
Mingchuan Yuan
Keyword(s):  
Spanning Tree ◽  
Closed Loop ◽  
Minimum Spanning Tree ◽  
Travelling Salesman Problem ◽  
Open Loop ◽  
Travelling Salesman ◽  
Elimination Algorithm ◽  
Number Of Iterations ◽  
Number Of Branches

Travelling salesman problem (TSP) has been widely studied for the classical closed loop variant but less attention has been paid to the open loop variant. Open loop solution has property of being also a spanning tree, although not necessarily the minimum spanning tree (MST). In this paper, we present a simple branch elimination algorithm that removes the branches from MST by cutting one link and then reconnecting the resulting subtrees via selected leaf nodes. The number of iterations equals to the number of branches (b) in the MST. Typically, b << n where n is the number of nodes. With O-Mopsi and Dots datasets, the algorithm reaches gap of 1.69% and 0.61 %, respectively. The algorithm is suitable especially for educational purposes by showing the connection between MST and TSP, but it can also serve as a quick approximation for more complex metaheuristics whose efficiency relies on quality of the initial solution.

Sign in / Sign up

Export Citation Format

Share Document