An Augmented Interaction Strategy For Designing Human-Machine Interfaces For Hydraulic Excavators

Lack of adequate information feedback and work visibility, and fatigue due to repetition have been identified as the major usability gaps in the human-machine interface (HMI) design of modern hydraulic excavators that subject operators to undue mental and physical workload, resulting in poor performance. To address these gaps, this work proposed an innovative interaction strategy, termed “augmented interaction”, for enhancing the usability of the hydraulic excavator. Augmented interaction involves the embodiment of heads-up display and coordinated control schemes into an efficient, effective and safe HMI. Augmented interaction was demonstrated using a framework consisting of three phases: Design, Implementation/Visualization, and Evaluation (D.IV.E). Guided by this framework, two alternative HMI design concepts (Design A: featuring heads-up display and coordinated control; and Design B: featuring heads-up display and joystick controls) in addition to the existing HMI design (Design C: featuring monitor display and joystick controls) were prototyped. A mixed reality seating buck simulator, named the Hydraulic Excavator Augmented Reality Simulator (H.E.A.R.S), was used to implement the designs and simulate a work environment along with a rock excavation task scenario. A usability evaluation was conducted with twenty participants to characterize the impact of the new HMI types using quantitative (task completion time, TCT; and operating error, OER) and qualitative (subjective workload and user preference) metrics. The results indicated that participants had a shorter TCT with Design A. For OER, there was a lower error probability due to collisions (PER1) with Design A, and lower error probability due to misses (PER2)with Design B. The subjective measures showed a lower overall workload and a high preference for Design B. It was concluded that augmented interaction provides a viable solution for enhancing the usability of the HMI of a hydraulic excavator

Position referenced force augmentation in teleoperated hydraulic manipulators operating under delayed and lossy networks: a pilot study.

Position error between motions of the master and slave end-effectors is inevitable as it originates from hard-to-avoid imperfections in controller design and model uncertainty. Moreover, when a slave manipulator is controlled through a delayed and lossy communication channel, the error between the desired motion originating from the master device and the actual movement of the slave manipulator end-effector is further exacerbated. This paper introduces a force feedback scheme to alleviate this problem by simply guiding the operator to slow down the haptic device motion and, in turn, allows the slave manipulator to follow the desired trajectory closely. Using this scheme, the master haptic device generates a force, which is proportional to the position error at the slave end-effector, and opposite to the operator's intended motion at the master site. Indeed, this force is a signal or cue to the operator for reducing the hand speed when position error, due to delayed and lossy network, appears at the slave site. Effectiveness of the proposed scheme is validated by performing experiments on a hydraulic telemanipulator setup developed for performing live-line maintenance. Experiments are conducted when the system operates under both dedicated and wireless networks. Results show that the scheme performs well in reducing the position error between the haptic device and the slave end-effector. Specifically, by utilizing the proposed force, the mean position error, for the case presented here, reduces by at least 92% as compared to the condition without the proposed force augmentation scheme. The scheme is easy to implement, as the only required on-line measurement is the angular displacement of the slave manipulator joints

Teleoperation of a service robot using a mobile device

Teleoperation is a concept born with the rapid evolution of technology, with an intuitive meaning "operate at a distance." The first teleoperation system was created in the mid 1950s, which were handled chemicals. Remote controlled systems are present nowadays in various types of applications. This dissertation presents the development of a mobile application to perform the teleoperation of a mobile service robot. The application integrates a distributed surveillance (the result of a research project QREN) and led to the development of a communication interface between the robot (the result of another QREN project) and the vigilance system. It was necessary to specify a communication protocol between the two systems, which was implemented over a communication framework 0MQ (Zero Message Queue). For the testing, three prototype applications were developed before to perform the test on the robot

磁性流体を用いたバックドライブ可能な油圧アクチュエータの開発

早大学位記番号:新7478早稲田大

Command and Control Systems for Search and Rescue Robots

The novel application of unmanned systems in the domain of humanitarian Search and Rescue (SAR) operations has created a need to develop specific multi-Robot Command and Control (RC2) systems. This societal application of robotics requires human-robot interfaces for controlling a large fleet of heterogeneous robots deployed in multiple domains of operation (ground, aerial and marine). This chapter provides an overview of the Command, Control and Intelligence (C2I) system developed within the scope of Integrated Components for Assisted Rescue and Unmanned Search operations (ICARUS). The life cycle of the system begins with a description of use cases and the deployment scenarios in collaboration with SAR teams as end-users. This is followed by an illustration of the system design and architecture, core technologies used in implementing the C2I, iterative integration phases with field deployments for evaluating and improving the system. The main subcomponents consist of a central Mission Planning and Coordination System (MPCS), field Robot Command and Control (RC2) subsystems with a portable force-feedback exoskeleton interface for robot arm tele-manipulation and field mobile devices. The distribution of these C2I subsystems with their communication links for unmanned SAR operations is described in detail. Field demonstrations of the C2I system with SAR personnel assisted by unmanned systems provide an outlook for implementing such systems into mainstream SAR operations in the future

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

Limited Information Shared Control and its Applications to Large Vehicle Manipulators

Diese Dissertation beschäftigt sich mit der kooperativen Regelung einer mobilen Arbeitsmaschine, welche aus einem Nutzfahrzeug und einem oder mehreren hydraulischen Manipulatoren besteht. Solche Maschinen werden für Aufgaben in der Straßenunterhaltungsaufgaben eingesetzt. Die Arbeitsumgebung des Manipulators ist unstrukturiert, was die Bestimmung einer Referenztrajektorie erschwert oder unmöglich macht. Deshalb wird in dieser Arbeit ein Ansatz vorgeschlagen, welcher nur das Fahrzeug automatisiert, während der menschliche Bediener ein Teil des Systems bleibt und den Manipulator steuert. Eine solche Teilautomatisierung des Gesamtsystems führt zu einer speziellen Klasse von Mensch-Maschine-Interaktionen, welche in der Literatur noch nicht untersucht wurde: Eine kooperative Regelung zwischen zwei Teilsystemen, bei der die Automatisierung keine Informationen von dem vom Menschen gesteuerten Teilsystem hat. Deswegen wird in dieser Arbeit ein systematischer Ansatz der kooperativen Regelung mit begrenzter Information vorgestellt, der den menschlichen Bediener unterstützen kann, ohne die Referenzen oder die Systemzustände des Manipulators zu messen. Außerdem wird ein systematisches Entwurfskonzept für die kooperative Regelung mit begrenzter Information vorgestellt. Für diese Entwurfsmethode werden zwei neue Unterklassen der sogenannten Potenzialspiele eingeführt, die eine systematische Berechnung der Parameter der entwickelten kooperativen Regelung ohne manuelle Abstimmung ermöglichen. Schließlich wird das entwickelte Konzept der kooperativen Regelung am Beispiel einer großen mobilen Arbeitsmaschine angewandt, um seine Vorteile zu ermitteln und zu bewerten. Nach der Analyse in Simulationen wird die praktische Anwendbarkeit der Methode in drei Experimenten mit menschlichen Probanden an einem Simulator untersucht. Die Ergebnisse zeigen die Überlegenheit des entwickelten kooperativen Regelungskonzepts gegenüber der manuellen Steuerung und der nicht-kooperativen Steuerung hinsichtlich sowohl der objektiven Performanz als auch der subjektiven Bewertung der Probanden. Somit zeigt diese Dissertation, dass die kooperative Regelung mobiler Arbeitsmaschinen mit den entwickelten theoretischen Konzepten sowohl hilfreich als auch praktisch anwendbar ist