Shorya Awtar

Abstract This paper introduces a new class of single-degree-of-freedom (DoF) compliant mechanisms that exhibit optimal bearing characteristics, defined by low stiffness in the out-of-plane motion direction, high stiffness in the in-plane bearing directions, and zero parasitic motion in the in-plane bearing directions. This new class features multi-layer arrangements of two thin, planar compliant mechanisms (referred to as diaphragm flexures) separated in the out-of-plane direction and strategically interconnected at several critical locations. Optimal bearing performance is not achievable in traditional single-layer diaphragm flexures. The only prior mult-ilayer design based on folded flexure beams, despite exhibiting optimal bearing characteristics, suffers from two major limitations: structural complexity and poor bearing stiffness in the in-plane rotational bearing direction. To address these limitations, this work presents a novel synergistic integration of two design innovations: (1) a new single-layer diaphragm flexure comprising nested flexure beams instead of conventional folded flexure beams and (2) two distinct multi-layer architectures between a pair of diaphragm flexures comprising nested beams, each incorporating a carefully designed combination of compliant and rigid elements and specifically tailored to overcome one of the fundamental limitations associated with the previous folded beam multi-layer design. Analytical models are derived for the bearing direction and motion direction stiffness of the proposed multi-layer designs that closely match finite element analysis (FEA) predictions, and the optimal bearing performance of these designs is demonstrated and thoroughly discussed.

With advances in autonomous vehicle technology and in-cabin occupant monitoring systems, prediction of motion sickness (MS) has emerged as a key challenge to improve passenger experience. In this paper, a framework for MS prediction is proposed leveraging classification algorithms and timeseries physiological data, including blood volume pulse, electrodermal activity, and neck surface electromyography. The dataset used for model training contains over 1500 min of in-vehicle data, three test conditions, and a range of subject demographics. Model predictions were able to achieve 81% accuracy for binary classification (sick or not sick) and 58% for ternary classification (low, moderate or high sickness). In addition, feature importance analysis identified electrodermal activity and surface electromyography as the most relevant data streams for MS prediction. Finally, the paper analyzed the temporal dependency of physiological data on MS response and found that physiological data can precede a subject's self-reporting of MS by up to 180 s.

Abstract Diaphragm flexures are widely used in various precision applications to generate guided motion along the out-of-plane directions and provide load bearing along the in-plane directions. The traditional Asymmetric Simple Beam (ASB) diaphragm flexure suffers from large parasitic rotation about the out-of-plane translation direction. The Asymmetric Folded Beam (AFB) design eliminates or minimizes the parasitic rotation seen in the ASB design and offers desirably low out-of-plane stiffness. However, its in-plane stiffness is undesirably low and exhibits a steep drop with increasing the out-of-plane displacement due to the under-constraint of the unsupported ends of the folded beams. This paper proposes a novel diaphragm flexure design, referred to as the Sandwich Asymmetric Folded Beam with Parallelogram Flexure Module in-plane interconnect (SAFB-PFM), that minimizes the under-constraint of the folded beams in the AFB design, thereby achieving a substantial improvement in the in-plane stiffness without compromising the out-of-plane stiffness. This novel design comprises a sandwich arrangement of two identical AFB diaphragm flexures spaced apart along the out-of-plane direction, with out-of-plane interconnects between the two corresponding diaphragms, the two corresponding frames, and every pair of the corresponding unsupported ends of the folded beams and an in-plane interconnect between the unsupported ends of each AFB layer. The optimal bearing performance of the SAFB-PFM design (i.e., high in-plane stiffness and low out-of-plane stiffness) is demonstrated via nonlinear finite element analysis (FEA) followed by several physical design observations. Additionally, FEA-based modal analysis is utilized to highlight the improved dynamic performance of the sandwich design compared to the single-layer AFB design.

Abstract Diaphragm flexures generate guided out-of-plane motion while providing in-plane load bearing for a broad range of precision applications. This paper presents a novel multi-layer diaphragm flexure design that exhibits optimal bearing performance (i.e. low stiffness in the out-of-plane direction and high stiffness in the in-plane directions) and nearly zero parasitic rotation about the out-of-plane translational direction, simultaneously. The new design consists of a multi-layer arrangement of two identical diaphragm flexures comprising “nested flexure beams”, spaced apart along the out-of-plane direction. The two corresponding diaphragms, the two corresponding ground frames, and every pair of the corresponding unsupported ends of the nested beams are interconnected between the upper and lower layers. Additionally, the unsupported ends of the nested beam are also interconnected within each respective upper and lower layer. Analytical models are presented for the in-plane and out-of-plane stiffness of the proposed design that closely match Finite Element Analysis (FEA) results. The novel design proposed in this paper offers a simpler interconnect structure compared to the previous design comprising folded flexure beams, facilitating the manufacturing and assembling processes and leading to a lighter sandwich design with more favorable dynamic performance.

Abstract This article investigates nonminimum phase zeros in the transfer function, between actuated load input and measured position output, of multi-degrees-of-freedom (DoF) undamped flexible systems. The transfer function of an undamped flexible system can be modally decomposed into second-order modes, where each mode is characterized by its modal residue and modal frequency. It is well known that when all the modal residue signs are the same, all the zeros of the undamped flexible system are minimum phase. However, it is not always possible to guarantee the same sign for all modal residues, given practical constraints on actuator and sensor placement. This article presents a new sufficient condition for the absence of nonminimum phase (NMP) zeros when all modal residue signs are not the same. First, a sufficient condition for the absence of only complex NMP zeros is derived in terms of the sequence of modal residue signs. Once this sufficient condition is obtained, the sufficient condition for the absence of all NMP zeros, i.e., complex as well as real NMP zeros, is derived. The efficacy of this sufficient condition is then demonstrated theoretically and experimentally via two case studies. These case studies show that the sufficient condition allows a large design space for the choice of physical parameters, is mathematically easy to use, is robust to parametric variations and modeling uncertainty, and is applicable even in the presence of a small amount of damping. These attributes make the sufficient condition useful in several motion control applications where the dynamic performance is limited by the presence of NMP zeros.

<div class="section abstract"><div class="htmlview paragraph">Technology development for enhancing passenger experience has gained attention in the field of autonomous vehicle (AV) development. A new possibility for occupants of AVs is performing productive tasks as they are relieved from the task of driving. However, passengers who execute non-driving-related tasks are more prone to experiencing motion sickness (MS). To understand the factors that cause MS, a tool that can predict the occurrence and intensity of MS can be advantageous. However, there is currently a lack of computational tools that predict passenger's MS state. Furthermore, the lack of real-time physiological data from vehicle occupants limits the types of sensory data that can be used for estimation under realistic implementations. To address this, a computational model was developed to predict the MS score for passengers in real time solely based on the vehicle's dynamic state. The model leverages self-reported MS scores and vehicle dynamics time series data from a previous study performed under realistic driving conditions. The data comprises 66 trials (1 trial = 1350s) and includes MS score (1-10 scale), static parameters (e.g., age, gender, MS susceptibility, etc.), cabin parameters (i.e., temperature, humidity), and vehicle's dynamic state (e.g., acceleration, angular velocity etc). The deep-learning models presented here include long short-term memory (LSTM) and nonlinear auto-regressive (NARX), which can create a time series mapping between vehicle sensor data, static parameters, and MS score. The predictive models were optimized in terms of their hyperparameters, and their results were validated by analyzing the conformance between actual and predicted MS scores. The NARX and LSTM models produced mean RMSE of 2.2 and 2.3, respectively. Both results are deemed acceptable based on the range of MS scores in the scale used. The developed model framework is a promising solution for estimating MS when only vehicle data is available.</div></div>

Abstract The previously presented beam constraint model (BCM) successfully captures pertinent nonlinearities to predict the constraint characteristics of beam flexures. This has been followed by multiple attempts to construct a more comprehensive framework comprising strain energy (SE) principles and complementary strain energy (CSE) principles. However, comprehensive results are still lacking in the current literature, especially in the validation of the CSE definition, fundamental relations between beam coefficients, further relationships between the SE and the CSE, and suitable examples. This article addresses all these gaps. The nonlinear CSE is derived using the principle of complementary virtual work for a planar beam undergoing intermediate deflections. This result is shown to be consistent with the load—displacement relations and the nonlinear strain energy formulation in the BCM. Furthermore, the current article also demonstrates for the first time that the SE and the CSE are interrelated through the gap energy, which is derived and formulated in terms of tip loads. Finally, this CSE expression is employed in the analysis of a fixed-guided mechanism. All results are validated to a high degree of accuracy via nonlinear finite element analysis.

Carsickness (CS) experienced by vehicle passengers is a critical unsolved challenge that impacts existing human-driven vehicles and may limit the adoption of future autonomous vehicles. If CS is reduced, then passengers can perform productive tasks during their commutes. Prior research has demonstrated that a preemptively triggered tilting seat system (TSS), i.e., a seat that tilts the passenger in the direction of the vehicle's turn, can reduce CS response. However, no previous investigations have studied the impact of TSS on passengers performing representative productive tasks when riding a real vehicle under realistic driving conditions. This paper addresses this gap by presenting a human subject study to quantify passenger CS response and assess their task performance in the presence of a preemptively triggered TSS. Twenty-nine healthy adults with varying levels of self-reported motion sickness susceptibility participated in the study across two test conditions. This is the first in-vehicle study that assessed both CS response and passenger task performance for a diverse sample of passengers under realistic driving conditions emulated on a closed test track. The results from this study demonstrated that a preemptively triggered TSS reduces CS scores for male passengers and has no negative influence on their productive task performance. The results also demonstrated that a preemptively triggered TSS did not have an effect on CS scores for female passengers but had a small positive influence on their productive task performance. In addition, the majority of the study participants (∼70%) indicated via a qualitative questionnaire that they would want a preemptively triggered TSS in their car.

Abstract This article investigates the nonminimum phase (NMP) zeros in the transfer function, between actuated load input and measured displacement output, of a multi-degrees-of-freedom (DoF) flexible system in the presence of proportional viscous damping. NMP zeros have a negative impact on the dynamics and control of flexible systems and therefore are generally undesirable. Viscous damping is one potential means to guarantee that no NMP zeros exist in the system. However, the impact of viscous damping on NMP zeros of multi-DoF flexible systems is not adequately studied or understood in the literature. To address this gap, a change of variable method is used to first establish a simple mathematical relationship between the zeros of a multi-DoF undamped flexible system and its proportionally damped counterpart. The “proportional” viscous damping model is used due to its practical amenability, conceptual simplicity, and ease of application. This mathematical relationship (between zeros of an undamped system and its damped counterpart) is used to derive the necessary and sufficient condition for the absence of NMP zeros in proportionally damped flexible systems. A graphical analysis of this necessary and sufficient condition is provided, which leads to the formulation of simple proportional damping strategies. A case study of a 4DoF flexible system is presented to demonstrate how a proportional viscous damping strategy can be used to simultaneously guarantee the absence of NMP zeros in multiple single-input single-output (SISO) transfer functions of a multi-DoF flexible system.

Abstract Parallelogram flexure mechanism (PFM) is a common flexure module that is widely used as a building block in the design and manufacturing of flexure-based XY motion stages that provide in-plane degrees-of-freedom (DoFs). In such motion stages, low in-plane stiffness along the DoF helps increase the DoF range of motion and reduce the actuation effort. At the same time, high out-of-plane stiffness is paramount to suppress out-of-plane parasitic motions, support heavy payloads, and mitigate the negative impacts of out-of-plane resonant modes. Achieving both of these design objectives simultaneously is extremely challenging in PFMs and flexure mechanisms comprising PFMs due to the inherent tradeoff between the in-plane and out-of-plane stiffnesses. This paper resolves this tradeoff by proposing a novel multi-layer PFM architecture, referred to as the sandwich PFM, that achieves significant improvements in the out-of-plane translational and rotational stiffnesses compared to conventional single-layer PFMs without impacting the in-plane DoF stiffness. Analytical models will be derived for the in-plane and out-of-plane stiffnesses of the sandwich PFM, which closely match the Finite Element Analysis (FEA) results. Several design insights into the performance of the sandwich PFM are discussed using the analytical stiffness models, and a general procedure is proposed to design a sandwich PFM.

Abstract High out-of-plane stiffness is crucial in flexure-based motion stages that offer in-plane Degrees of Freedom (DoF). High out-of-plane stiffness helps support large payloads, suppress parasitic motions, and mitigate the adverse effects of out-of-plane vibration modes. Low in-plane stiffness is also essential because it increases the DoF range of motion and reduces the actuation effort. Increasing the out-of-plane stiffness and decreasing the in-plane stiffness simultaneously in flexure mechanisms is challenging because both these stiffness arise from the same flexible elements leading to an inherent tradeoff. This paper resolves this tradeoff by proposing a novel sandwich flexure blade architecture that improves the out-of-plane stiffness without affecting the in-plane stiffness. Closed-form analytical models are presented for the out-of-plane translational and rotational stiffness of the single-layer (or conventional) flexure blade and the novel sandwich flexure blade based on Timoshenko beam theory that closely match with Finite Element Analysis (FEA) results. Superior performance of the sandwich flexure blade over the conventional flexure blades is demonstrated and several design insights into the performance of the sandwich flexure blades are discussed based on the analytical stiffness models.

Abstract High-precision and high-speed requirements in flexure-based positioning systems require stringent dynamic performance. In the presence of geometric non-linearities, which are relevant in large stroke flexure mechanisms, a standard approach is to linearize the system dynamics about an operating point and then design suitable controllers. Therefore, the first step in this subsequent dynamic analysis, is to have static equilibrium conditions of the flexure mechanism that can serve as the operating point. With this motivation, the objective of this paper is to propose a nonlinear static model for a specific XY flexure mechanism capable of decoupled motion along two orthogonal axes. This XY flexure mechanism is of practical use in high-precision high-speed positioning systems. Initially, the generalized coordinates of the flexure mechanism are chosen from the various displacement coordinates of the system. The strain energy and generalized forces of the flexure depend not only on the generalized coordinates but also on other displacement coordinates. This complicates the application of the principle of virtual work. To address this complexity, we utilize the fact that other displacement components of the system implicitly depend on the generalized coordinates due to nonlinear constraints arising from the geometric nonlinearities associated with beam arc-length conservation. By considering this implicit dependence when applying derivatives in the principle of virtual work, we can derive the nonlinear equilibrium equations governing the static behavior of the flexure mechanism. This approach for arriving at a static model for the XY flexure is then generalized into a step-by-step procedure, capable of deriving the governing nonlinear static equations of a diverse class of flexure mechanisms. A physical understanding of the system is then employed to solve these equations to obtain the operating point for uniaxial loading. Resulting expressions are then used in a subsequent analysis with perturbation expansions to obtain closed-form, highly accurate solutions for the operating point of the XY flexure under biaxial loading. The results are validated through numerical simulations and Finite Element Analysis.

Abstract It is well known that real nonminimum phase (RNMP) zeros impose a tradeoff between the settling time and undershoot in the step response of flexible systems. Existing methods to alleviate this tradeoff predominantly rely on various advanced control strategies without delving into a broader mechatronic approach that combines physical system and control system design. To address this gap, this article proposes a proportional viscous damping-based physical system design in combination with feedback control and prefilter design. First, the effect of proportional viscous damping on RNMP zeros of flexible systems is established to propose a damping strategy that pushes all the RNMP zeros further away from the imaginary axis. Then, a step-by-step mechatronic system design process is presented to apply this damping strategy along with a full-state feedback control strategy and prefilter to a multi-degree-of-freedom (DoF) flexible system. The application of this design process yields simultaneous improvement in the settling time and undershoot in the step response of this flexible system.

Abstract Frog-leg robots are widely used for wafer-handling in semiconductor manufacturing. A typical frog-leg robot uses a magnetic coupler to achieve contactless transmission of motion between its driving motors, which operate at atmospheric pressure, and its end effector (blade) which operates within a vacuum chamber. However, the magnetic coupler is a low-stiffness transmission element that induces residual vibration during fast motions of the robot. Excessive residual vibration can cause collisions between the fragile wafer carried by the robot and cassette, hence damaging the wafer. While this problem could be solved by slowing down the robot, it comes at the cost of reduced productivity, which is undesirable. Therefore, this paper reports a preliminary investigation into input shaping (a popular vibration compensation technique) as a tool to reduce residual vibration of a frog-leg robot during high-speed motions. Two types of motions of the robot are considered: rotation and extension. A standard input shaper is shown to be very effective for mitigating residual vibration caused by rotational motion but is much less effective for extensional motion. The rationale is that the resonance frequencies of the robot are constant during rotation but they vary significantly during extension, hence reducing the effectiveness of standard input shaping. This necessitates the use of more advanced input shapers that can handle varying resonance frequencies to mitigate residual vibration during extensional motion in future work.

Motion sickness when traveling in a vehicle is a common condition that afflicts one in three adults in the US. Moreover, passengers who are not driving the vehicle experience such motion sickness more acutely compared to the driver of the vehicle. This is due to the driver’s ability to make anticipatory corrections when initiating a driving action that involves acceleration (e.g. speeding up, breaking, or taking turns). These anticipatory corrections by the driver (such as tightening their abdominal core muscles when braking or leaning their body/head into the direction of the turn when turning) help prepare the driver for the accelerations associated with the driving actions slightly ahead of time, whereas the passenger ends up passively reacting to these driving actions. With the impending transformation in ground transportation due to autonomous vehicles, where every occupant is a passive passenger, the deleterious effects of motion sickness on the passenger comfort and productivity during their commute is expected to be significant. The goal of this research project was to develop an experimental vehicle testbed and passenger instrumentation for testing motion sickness mitigation solutions that employ preemptive stimuli provided to passengers in autonomous vehicles. Towards this goal, this project has led to the development of several key experimental modules and testing protocols, including a vehicle testbed comprising an active seat (with embedded haptic motors) for providing preemptive stimuli, extensive instrumentation to measure the states of the vehicle and the passenger, an Mcity drive path that is representative of city and highway driving, an automatic triggering scheme to preemptively actuate the haptic stimuli based on this drive path, and an IRB approved human subject testing protocol. The vehicle was designed to emulate an autonomous vehicle riding experience for the passenger. This experimental setup was then used to conduct a human subject study to quantify passenger motion sickness response while performing representative task along with preemptively triggered haptic stimuli. Twenty-four healthy adults with varying levels of self-reported motion sickness susceptibility participated in the study on the Mcity test track in the above vehicle testbed. The data showed a statistically significant reduction in motion sickness as a result of preemptive haptic stimuli.

Mitigating car sickness (CS) or motion sickness is a key adoption challenge that needs to be solved to realize the future that autonomous vehicles promise. It is known that while drivers of vehicles do not get CS, passengers often do. A driver can anticipate the vehicle motion as they are in control of it, and can take corrective actions which ensure they do not get CS. In autonomous vehicles there will be no drivers, and all passengers will be susceptible to CS. Prior work has shown that haptic stimuli (i.e., vibrations) can be used to provide vehicle motion information to passengers to reduce CS. However, there have been limited investigations of this stimuli being provided to passengers preemptively (i.e., in anticipation of vehicle motion), just like a driver. This paper presents the results from a pilot study (6 participants) investigating the efficacy of preemptively triggered haptic stimuli in reducing CS. Unlike prior research, passenger task performance is also investigated in this study to determine if there is any influence on task performance due to preemptive haptic stimuli. The results from the pilot study show that preemptively triggered haptic stimuli can help reduce CS while having no negative effects on task performance.

OBJECTIVE: This study proposed a model to predict passenger motion sickness under the presence of a visual-vestibular conflict and assessed its performance with respect to previously recorded experimental data. BACKGROUND: While several models have been shown useful to predict motion sickness under repetitive motion, improvements are still desired in terms of predicting motion sickness in realistic driving conditions. There remains a need for a model that considers angular and linear visual-vestibular motion inputs in three dimensions to improve prediction of passenger motion sickness. METHOD: The model combined the subjective vertical conflict theory and human motion perception models. The proposed model integrates visual and vestibular sensed 6 DoF motion signals in a novel architecture. RESULTS: Model prediction results were compared to motion sickness data obtained from studies conducted in motion simulators as well as on-road vehicle testing, yielding trends that are congruent with observed results in both cases. CONCLUSION: The model demonstrated the ability to predict trends in motion sickness response for conditions in which a passenger performs a task on a handheld device versus facing forward looking ahead under realistic driving conditions. However, further analysis across a larger population is necessary to better assess the model's performance. APPLICATION: The proposed model can be used as a tool to predict motion sickness under different levels of visual-vestibular conflict. This can be leveraged to design interventions capable of mitigating passenger motion sickness. Further, this model can provide insights that aid in the development of passenger experiences inside autonomous vehicles.