Faster, Higher, and Greener: Vehicular Optimal Control

Limebeer, D.J.N.; Rao, Anil V.

doi:10.1109/mcs.2014.2384951

Cited by 34 publications

(4 citation statements)

References 73 publications

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“…A unique solution for the tyre loads can be obtained by adding a suspension-related roll balance relationship [13], as:…”

Section: ) Algebraic Constraintsmentioning

confidence: 99%

DEFT - A Scaled Electric Vehicle Platform for Testing Autonomous Driving Algorithm

Kumar,

Pasumarthy,

Bhatt

2024

Preprint

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Scaled-down vehicles provide a controlled and repeatable environment for testing autonomous driving algorithms, expediting development while mitigating risks associated with full-scale vehicle testing. This paper introduces a meticulously designed scaled-down electric vehicle, emphasizing vehicle state measurement, precise control, perception sensing, and electric safety. Our approach utilizes actuators with feedback, provides enhanced reliability and precision, and torque across all speed ranges, in contrast to conventional scaled platforms built with actuators of radio-controlled cars. Apart from the conventional sensors used in the existing scaled platforms, our vehicle incorporates novel sensor modules to measure wheel angular velocities, steering angles, and battery cell voltages, which can also be seamlessly integrated into these platforms. We demonstrate the vehicle’s motion with manual and autonomous operation and showcase its features for validation.

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“…A unique solution for the tyre loads can be obtained by adding a suspension-related roll balance relationship [13], as:…”

Section: ) Algebraic Constraintsmentioning

confidence: 99%

DEFT - A Scaled Electric Vehicle Platform for Testing Autonomous Driving Algorithm

Kumar,

Pasumarthy,

Bhatt

2024

Preprint

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“…1, 3.2, and 3.3, respectively. simulation to maintain system stability, is unnecessary since time stepping is not performed by implicit simulation. An overview of various numerical methods for solving optimal control problems, along with a brief discussion of the advantages and disadvantages of each, can be found in Limebeer and Rao (2015). We investigated how well the predictions worked using three different control situations: joint torque controls (5 per legtermed "torque-driven"), muscle activation controls (35 per legtermed "activation-driven"), and muscle synergy controls (5 per leg -termed "synergy-driven").…”

Section: Optimal Control Walking Predictionsmentioning

confidence: 99%

Applications of Synergies in Human Machine Interfaces

Vinjamuri¹,

Mao²,

Maybhate³

2019

Frontiers Research Topics

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Application of neural machine interface in individuals with chronic hemiparetic stroke is regarded as a great challenge, especially for classification of the hand opening and grasping during a functional upper extremity movement such as reach-to-grasp. The overall accuracy of classifying hand movements, while actively lifting the paretic arm, is subject to a significant reduction compared to the accuracy when the arm is fully supported. Such a reduction is believed to be due to the expression of flexion synergy, which couples shoulder abduction (SABD) with elbow/wrist and finger flexion, and is common in up to 60% of the stroke population. Little research has been done to develop methods to reduce the impact of flexion synergy on the classification of hand opening and grasping. In this study, we proposed a novel approach to classify hand opening and grasping in the context of the flexion synergy using a wavelet coherence-based filter. We first identified the frequency ranges where the coherence between the SABD muscle and wrist/finger flexion muscles is significant in each participant, and then removed the synergy-induced electromyogram (EMG) component with a subject-specific and muscle-specific coherence-based filter. The new approach was tested in 21 stroke individuals with moderate to severe motor impairments. Employing the filter, 14 participants gained improvement in classification accuracy with a range of 0.1 to 14%, while four showed 0.3 to 1.2% reduction. The remaining three participants were excluded from comparison due to the lack of significant coherence, thus no filters were applied. The improvement in classification accuracy is significant (p = 0.017) when the SABD loading equals 50% of the maximal torque. Our findings suggest that the coherence-based filters can reduce the impact of flexion synergy by removing the synergy-induced EMG component and have the potential to improve the overall classification accuracy of hand movements in individuals with poststroke flexion synergy.

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“…Optimal control techniques have been used extensively in the literature to predict the minimum-time manoeuvring of road vehicles, both in the case of cars and motorcycles [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]. The typical set-up includes the definition of the circuit geometry (curvatures, width, etc.)…”

Section: Introductionmentioning

confidence: 99%

Optimal recovery manoeuvres of racing motorcycles

Marconi

Massaro

2022

Meccanica

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The focus of this work is on the optimal recovery manoeuvres of racing vehicles, which are here defined as the manoeuvres that need be performed in order to complete the lap in the minimum time, after a driving error occurs. The driving errors considered are speed excess and trajectory deviations, with respect to the baseline conditions. The baseline conditions are those giving the minimum lap time, and are vehicle and track dependent. The practical applications of the methodology proposed include the estimation of the driving errors that can be recovered while remaining within the racetrack borders, and the estimation of the minimum asphalted run-off area that need be provided to recover from driving errors of given magnitude. An example of application is given for a racing motorcycle on the Mugello circuit.

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Faster, Higher, and Greener: Vehicular Optimal Control

Cited by 34 publications

References 73 publications

DEFT - A Scaled Electric Vehicle Platform for Testing Autonomous Driving Algorithm

DEFT - A Scaled Electric Vehicle Platform for Testing Autonomous Driving Algorithm

Applications of Synergies in Human Machine Interfaces

Optimal recovery manoeuvres of racing motorcycles

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