Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains

With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented.First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations

An Active Safety System for Low-Speed Bus Braking Assistance

Accidents in which buses or coaches are involved cause thousands of injuries and fatalities every year. To reduce their number and severity, the paper describes an Advanced Driver Assistance Systems (ADAS) based on a haptic throttle pedal and emergency braking. It also proposes a computationally efficient algorithm with a methodology based on three main concepts: a simplified but accurate vehicle model; an efficient collision detection system considering driver's intention and pedestrians wandering around the vehicle; and a risk evaluation system to generate warnings and emergency braking signals. Finally, the performance of the proposed ADAS is validated using a driving simulation cabin with a very realistic urban scenario and original elements from real buses. The results show a statistically significant improvement in safety, as the number of collisions and high risk situations are clearly minimized, reaction time to press the brake pedal is improved and time to collision increased in emergency situations. Implementation of the proposed ADAS into city buses would potentially improve safety, reducing the frequency and severity of accidents with pedestrians.This work was supported in part by Ministry of Science and Innovation of Spain through the SAFEBUS Project "Sistemas Avanzados de Seguridad Integral en Autobuses" under Grant IPT-2011-1165-370000 and the SAFETRANS Project "Sistemas de Conduccion Segura de Vehiculos de Transporte de Pasajeros y Materiales con Asistencia Haptica/Audiovisual e Interfaces Biomedicas" under Grant DPI2013-42302-R and in part by the Generalitat Valenciana, Programa VALi+d (ACIF/2010/206). The Associate Editor for this paper was E. Kosmatopoulos.Girbés, V.; Armesto Ángel, L.; Dols Ruiz, JF.; Tornero Montserrat, J. (2017). An Active Safety System for Low-Speed Bus Braking Assistance. IEEE Transactions on Intelligent Transportation Systems. 18(2):377-387. https://doi.org/10.1109/TITS.2016.2573921S37738718

Clothoid-based Planning and Control in Intelligent Vehicles (Autonomous and Manual-Assisted Driving)

[EN] Nowadays, there are many electronic products that incorporate elements and features coming from the research in the field of mobile robotics. For instance, the well-known vacuum cleaning robot Roomba by iRobot, which belongs to the field of service robotics, one of the most active within the sector. There are also numerous autonomous robotic systems in industrial warehouses and plants. It is the case of Autonomous Guided Vehicles (AGVs), which are able to drive completely autonomously in very structured environments. Apart from industry and consumer electronics, within the automotive field there are some devices that give intelligence to the vehicle, derived in most cases from advances in mobile robotics. In fact, more and more often vehicles incorporate Advanced Driver Assistance Systems (ADAS), such as navigation control with automatic speed regulation, lane change and overtaking assistant, automatic parking or collision warning, among other features. However, despite all the advances there are some problems that remain unresolved and can be improved. Collisions and rollovers stand out among the most common accidents of vehicles with manual or autonomous driving. In fact, it is almost impossible to guarantee driving without accidents in unstructured environments where vehicles share the space with other moving agents, such as other vehicles and pedestrians. That is why searching for techniques to improve safety in intelligent vehicles, either autonomous or manual-assisted driving, is still a trending topic within the robotics community. This thesis focuses on the design of tools and techniques for planning and control of intelligent vehicles in order to improve safety and comfort. The dissertation is divided into two parts, the first one on autonomous driving and the second one on manual-assisted driving. The main link between them is the use of clothoids as mathematical formulation for both trajectory generation and collision detection. Among the problems solved the following stand out: obstacle avoidance, rollover avoidance and advanced driver assistance to avoid collisions with pedestrians.[ES] En la actualidad se comercializan infinidad de productos de electrónica de consumo que incorporan elementos y características procedentes de avances en el sector de la robótica móvil. Por ejemplo, el conocido robot aspirador Roomba de la empresa iRobot, el cual pertenece al campo de la robótica de servicio, uno de los más activos en el sector. También hay numerosos sistemas robóticos autónomos en almacenes y plantas industriales. Es el caso de los vehículos autoguiados (AGVs), capaces de conducir de forma totalmente autónoma en entornos muy estructurados. Además de en la industria y en electrónica de consumo, dentro del campo de la automoción también existen dispositivos que dotan de cierta inteligencia al vehículo, derivados la mayoría de las veces de avances en robótica móvil. De hecho, cada vez con mayor frecuencia los vehículos incorporan sistemas avanzados de asistencia al conductor (ADAS por sus siglas en inglés), tales como control de navegación con regulación automática de velocidad, asistente de cambio de carril y adelantamiento, aparcamiento automático o aviso de colisión, entre otras prestaciones. No obstante, pese a todos los avances siguen existiendo problemas sin resolver y que pueden mejorarse. La colisión y el vuelco destacan entre los accidentes más comunes en vehículos con conducción tanto manual como autónoma. De hecho, la dificultad de conducir en entornos desestructurados compartiendo el espacio con otros agentes móviles, tales como coches o personas, hace casi imposible garantizar la conducción sin accidentes. Es por ello que la búsqueda de técnicas para mejorar la seguridad en vehículos inteligentes, ya sean de conducción autónoma o manual asistida, es un tema que siempre está en auge en la comunidad robótica. La presente tesis se centra en el diseño de herramientas y técnicas de planificación y control de vehículos inteligentes, para la mejora de la seguridad y el confort. La disertación se ha dividido en dos partes, la primera sobre conducción autónoma y la segunda sobre conducción manual asistida. El principal nexo de unión es el uso de clotoides como elemento de generación de trayectorias y detección de colisiones. Entre los problemas que se resuelven destacan la evitación de obstáculos, la evitación de vuelcos y la asistencia avanzada al conductor para evitar colisiones con peatones.[CA] En l'actualitat es comercialitzen infinitat de productes d'electrònica de consum que incorporen elements i característiques procedents d'avanços en el sector de la robòtica mòbil. Per exemple, el conegut robot aspirador Roomba de l'empresa iRobot, el qual pertany al camp de la robòtica de servici, un dels més actius en el sector. També hi ha nombrosos sistemes robòtics autònoms en magatzems i plantes industrials. És el cas dels vehicles autoguiats (AGVs), els quals són capaços de conduir de forma totalment autònoma en entorns molt estructurats. A més de en la indústria i en l'electrònica de consum, dins el camp de l'automoció també existeixen dispositius que doten al vehicle de certa intel·ligència, la majoria de les vegades derivats d'avanços en robòtica mòbil. De fet, cada vegada amb més freqüència els vehicles incorporen sistemes avançats d'assistència al conductor (ADAS per les sigles en anglés), com ara control de navegació amb regulació automàtica de velocitat, assistent de canvi de carril i avançament, aparcament automàtic o avís de col·lisió, entre altres prestacions. No obstant això, malgrat tots els avanços segueixen existint problemes sense resoldre i que poden millorar-se. La col·lisió i la bolcada destaquen entre els accidents més comuns en vehicles amb conducció tant manual com autònoma. De fet, la dificultat de conduir en entorns desestructurats compartint l'espai amb altres agents mòbils, tals com cotxes o persones, fa quasi impossible garantitzar la conducció sense accidents. És per això que la recerca de tècniques per millorar la seguretat en vehicles intel·ligents, ja siguen de conducció autònoma o manual assistida, és un tema que sempre està en auge a la comunitat robòtica. La present tesi es centra en el disseny d'eines i tècniques de planificació i control de vehicles intel·ligents, per a la millora de la seguretat i el confort. La dissertació s'ha dividit en dues parts, la primera sobre conducció autònoma i la segona sobre conducció manual assistida. El principal nexe d'unió és l'ús de clotoides com a element de generació de trajectòries i detecció de col·lisions. Entre els problemes que es resolen destaquen l'evitació d'obstacles, l'evitació de bolcades i l'assistència avançada al conductor per evitar col·lisions amb vianants.Girbés Juan, V. (2016). Clothoid-based Planning and Control in Intelligent Vehicles (Autonomous and Manual-Assisted Driving) [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/65072TESI

Effect of Fixed and sEMG-Based Adaptive Shared Steering Control on Distracted Driver Behavior

Driver distraction is a well-known cause for traffic collisions worldwide. Studies have indicated that shared steering control, which actively provides haptic guidance torque on the steering wheel, effectively improves the performance of distracted drivers. Recently, adaptive shared steering control based on the forearm muscle activity of the driver has been developed, although its effect on distracted driver behavior remains unclear. To this end, a high-fidelity driving simulator experiment was conducted involving 18 participants performing double lane change tasks. The experimental conditions comprised two driver states: attentive and distracted. Under each condition, evaluations were performed on three types of haptic guidance: none (manual), fixed authority, and adaptive authority based on feedback from the forearm surface electromyography of the driver. Evaluation results indicated that, for both attentive and distracted drivers, haptic guidance with adaptive authority yielded lower driver workload and reduced lane departure risk than manual driving and fixed authority. Moreover, there was a tendency for distracted drivers to reduce grip strength on the steering wheel to follow the haptic guidance with fixed authority, resulting in a relatively shorter double lane change duration

Audio Focus: Interactive spatial sound coupled with haptics to improve sound source location in poor visibility

International audienceIn an effort to simplify human resource management and reduce costs, control towers are now more and more designed to not be implanted directly on the airport but remotely. This concept, known as Remote Control Tower, offers a “digital” working context because the view on the runways is broadcast remotely via cameras, which are located on the physical airport. This offers researchers and engineers the possibility to develop novel interaction techniques. But this technology relies on the sense of sight, which is largely used to give the operator information and interaction, and which is now becoming overloaded. In this paper, we focus on the design and the testing of new interaction forms that rely on the human senses of hearing and touch. More precisely, our study aims at quantifying the contribution of a multimodal interaction technique based on spatial sound and vibrotactile feedback to improve aircraft location. Applied to Remote Tower environment, the final purpose is to enhance Air Traffic Controller's perception and increase safety. Three different interaction modalities have been compared by involving 22 Air Traffic Controllers in a simulated environment. The experimental task consisted in locating aircraft in different airspace positions by using the senses of hearing and touch through two visibility conditions. In the first modality (spatial sound only), the sound sources (e.g. aircraft) had the same amplification factor. In the second modality (called Audio Focus), the amplification factor of the sound sources located along the participant's head sagittal axis was increased, while the intensity of the sound sources located outside this axis was decreased. In the last modality, Audio Focus was coupled with vibrotactile feedback to indicate in addition the vertical positions of aircraft. Behavioral (i.e. accuracy and response times measurements) and subjective (i.e. questionnaires) results showed significantly higher performance in poor visibility when using Audio Focus interaction. In particular, interactive spatial sound gave the participants notably higher accuracy in degraded visibility compared to spatial sound only. This result was even better when coupled with vibrotactile feedback. Meanwhile, response times were significantly longer when using Audio Focus modality (coupled with vibrotactile feedback or not), while remaining acceptably short. This study can be seen as the initial step in the development of a novel interaction technique that uses sound as a means of location when the sense of sight alone is not enough

An Empirical Assessment of Audio/Visual/Haptic Alerts and Warnings to Mitigate Risk of Phishing Susceptibility in Emails on Mobile Devices

Phishing emails present a threat to both personal and organizational data. Phishing is a cyber-attack using social engineering. About 94% of cybersecurity incidents are due to phishing and/or social engineering. A significant volume of prior literature documented that users are continuing to click on phishing links in emails, even after phishing awareness training. It appears there is a strong need for creative ways to alert and warn users to signs of phishing in emails. The main goal of the experiments in this study was to measure participants’ time for recognizing signs of phishing in emails, thus, reducing susceptibility to phishing in emails on mobile devices. This study included three phases. The first phase included 32 Subject Matter Experts (SMEs) that provided feedback on the top signs of phishing in emails, audio/visual/haptic pairings with the signs of phishing, and developmental constructs toward a phishing alert and warning system. The second phase included a pilot study with five participants to validate a phishing alert and warning system prototype. The third phase included delivery of the Phishing Alert and Warning System, (PAWS Mobile App ™) with 205 participants. The results of the first phase aligned the constructs for the alert and warning system. A female voice-over warning was chosen by the SMEs as well as visual icon alerts for the top signs of phishing in emails. This study designed, developed, as well as empirically tested the PAWS Mobile App, that alerted and warned participants to the signs of phishing in emails on mobile devices. PAWS displayed a randomized series of 20 simulated emails to participants with varying displays of either no alerts and warnings, or a combination of alerts and warnings. The results indicated audio alerts and visual warnings potentially lower phishing susceptibility in emails. Audio and visual warnings appeared to have assisted the study participants in noticing phishing emails more easily, and in less time than without audio and visual warnings. The results of this study also indicated alerts and warnings assisted participants in noticing distinct signs of phishing in the simulated phishing emails viewed. This study implicates phishing email alerts and warnings applied and configured to email applications may play a significant role in the reduction of phishing susceptibility

Enhanced online programming for industrial robots

The use of robots and automation levels in the industrial sector is expected to grow, and is driven by the on-going need for lower costs and enhanced productivity. The manufacturing industry continues to seek ways of realizing enhanced production, and the programming of articulated production robots has been identified as a major area for improvement. However, realizing this automation level increase requires capable programming and control technologies. Many industries employ offline-programming which operates within a manually controlled and specific work environment. This is especially true within the high-volume automotive industry, particularly in high-speed assembly and component handling. For small-batch manufacturing and small to medium-sized enterprises, online programming continues to play an important role, but the complexity of programming remains a major obstacle for automation using industrial robots. Scenarios that rely on manual data input based on real world obstructions require that entire production systems cease for significant time periods while data is being manipulated, leading to financial losses. The application of simulation tools generate discrete portions of the total robot trajectories, while requiring manual inputs to link paths associated with different activities. Human input is also required to correct inaccuracies and errors resulting from unknowns and falsehoods in the environment. This study developed a new supported online robot programming approach, which is implemented as a robot control program. By applying online and offline programming in addition to appropriate manual robot control techniques, disadvantages such as manual pre-processing times and production downtimes have been either reduced or completely eliminated. The industrial requirements were evaluated considering modern manufacturing aspects. A cell-based Voronoi generation algorithm within a probabilistic world model has been introduced, together with a trajectory planner and an appropriate human machine interface. The robot programs so achieved are comparable to manually programmed robot programs and the results for a Mitsubishi RV-2AJ five-axis industrial robot are presented. Automated workspace analysis techniques and trajectory smoothing are used to accomplish this. The new robot control program considers the working production environment as a single and complete workspace. Non-productive time is required, but unlike previously reported approaches, this is achieved automatically and in a timely manner. As such, the actual cell-learning time is minimal

Development of a workload estimator: The influence of surrounding traffic behaviour on driver workload and performance

The consumers’ increasing desire to be connected at all times and the advancement of integrated functionality within the vehicle, increases the risk that drivers could be faced with information overload while driving. Given the importance of human interaction with technology within the vehicle, automobile manufacturers are introducing workload manager systems within the vehicles to help prevent driver overload. However the ability of the system to decide in a timely manner requires anticipation of changes in workload, depending on the capacity of the driver and matching it with the demand expected from the driving task such as the dynamic traffic environment. In relation to the need to understand the influence of traffic demand on driver workload, the work here comprises the systematic manipulation of traffic complexity and exploration of workload measures to highlight which are sensitive to primary task demand manipulated. A within-subjects design was used in the studies explored in this thesis to allow comparison between different manipulated traffic conditions. In the first simulator test, the ability of various objective and subjective workload measures to tap into drivers’ momentary workload was examined. Following the identification of a subjective measure that was sensitive to the influence of lane changes performed by neighbouring vehicle on drivers’ momentary workload, the characteristics of the lane change were explored in the subsequent studies involving single and dual-task conditions. Overall, these studies suggested suppression of non-urgent communications by a workload manager during safety-critical conditions involving critical cut-ins would be advantageous to both younger and older drivers. This thesis offers a novel and valuable contribution to the design of a workload estimator so as to ensure that the driving demand is always within drivers’ capacity to avoid driver overload. Results of these studies have also highlighted the utility of vehicle-based sensor data in improving workload manager functionality

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility