A Novel Predictor Based Framework to Improve Mobility of High Speed Teleoperated Unmanned Ground Vehicles

Teleoperated Unmanned Ground Vehicles (UGVs) have been widely used in applications when driver safety, mission eciency or mission cost is a major concern. One major challenge with teleoperating a UGV is that communication delays can significantly affect the mobility performance of the vehicle and make teleoperated driving tasks very challenging especially at high speeds. In this dissertation, a predictor based framework with predictors in a new form and a blended architecture are developed to compensate effects of delays through signal prediction, thereby improving vehicle mobility performance. The novelty of the framework is that minimal information about the governing equations of the system is required to compensate delays and, thus, the prediction is robust to modeling errors. This dissertation first investigates a model-free solution and develops a predictor that does not require information about the vehicle dynamics or human operators' motion for prediction. Compared to the existing model-free methods, neither assumptions about the particular way the vehicle moves, nor knowledge about the noise characteristics that drive the existing predictive filters are needed. Its stability and performance are studied and a predictor design procedure is presented. Secondly, a blended architecture is developed to blend the outputs of the model-free predictor with those of a steering feedforward loop that relies on minimal information about vehicle lateral response. Better prediction accuracy is observed based on open-loop virtual testing with the blended architecture compared to using either the model-free predictors or the model-based feedforward loop alone. The mobility performance of teleoperated vehicles with delays and the predictor based framework are evaluated in this dissertation with human-in-the-loop experiments using both simulated and physical vehicles in teleoperation mode. Predictor based framework is shown to provide a statistically significant improvement in vehicle mobility and drivability in the experiments performed.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146026/1/zhengys_1.pd

Unlimited-wokspace teleoperation

Thesis (Master)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2012Includes bibliographical references (leaves: 100-105)Text in English; Abstract: Turkish and Englishxiv, 109 leavesTeleoperation is, in its brief description, operating a vehicle or a manipulator from a distance. Teleoperation is used to reduce mission cost, protect humans from accidents that can be occurred during the mission, and perform complex missions for tasks that take place in areas which are difficult to reach or dangerous for humans. Teleoperation is divided into two main categories as unilateral and bilateral teleoperation according to information flow. This flow can be configured to be in either one direction (only from master to slave) or two directions (from master to slave and from slave to master). In unlimited-workspace teleoperation, one of the types of bilateral teleoperation, mobile robots are controlled by the operator and environmental information is transferred from the mobile robot to the operator. Teleoperated vehicles can be used in a variety of missions in air, on ground and in water. Therefore, different constructional types of robots can be designed for the different types of missions. This thesis aims to design and develop an unlimited-workspace teleoperation which includes an omnidirectional mobile robot as the slave system to be used in further researches. Initially, an omnidirectional mobile robot was manufactured and robot-operator interaction and efficient data transfer was provided with the established communication line. Wheel velocities were measured in real-time by Hall-effect sensors mounted on robot chassis to be integrated in controllers. A dynamic obstacle detection system, which is suitable for omnidirectional mobility, was developed and two obstacle avoidance algorithms (semi-autonomous and force reflecting) were created and tested. Distance information between the robot and the obstacles was collected by an array of sensors mounted on the robot. In the semi-autonomous teleoperation scenario, distance information is used to avoid obstacles autonomously and in the force-reflecting teleoperation scenario obstacles are informed to the user by sending back the artificially created forces acting on the slave robot. The test results indicate that obstacle avoidance performance of the developed vehicle with two algorithms is acceptable in all test scenarios. In addition, two control models were developed (kinematic and dynamic control) for the local controller of the slave robot. Also, kinematic controller was supported by gyroscope

The Underpinnings of Workload in Unmanned Vehicle Systems

This paper identifies and characterizes factors that contribute to operator workload in unmanned vehicle systems. Our objective is to provide a basis for developing models of workload for use in design and operation of complex human-machine systems. In 1986, Hart developed a foundational conceptual model of workload, which formed the basis for arguably the most widely used workload measurement techniquethe NASA Task Load Index. Since that time, however, there have been many advances in models and factor identification as well as workload control measures. Additionally, there is a need to further inventory and describe factors that contribute to human workload in light of technological advances, including automation and autonomy. Thus, we propose a conceptual framework for the workload construct and present a taxonomy of factors that can contribute to operator workload. These factors, referred to as workload drivers, are associated with a variety of system elements including the environment, task, equipment and operator. In addition, we discuss how workload moderators, such as automation and interface design, can be manipulated in order to influence operator workload. We contend that workload drivers, workload moderators, and the interactions among drivers and moderators all need to be accounted for when building complex, human-machine systems

A State Estimation Approach for a Skid-Steered Off-Road Mobile Robot

This thesis presents a novel state estimation structure, a hybrid extended Kalman filter/Kalman filter developed for a skid-steered, six-wheeled, ARGO® all-terrain vehicle (ATV). The ARGO ATV is a teleoperated unmanned ground vehicle (UGV) custom fitted with an inertial measurement unit, wheel encoders and a GPS. In order to enable the ARGO for autonomous applications, the proposed hybrid EKF/KF state estimator strategy is combined with the vehicle’s sensor measurements to estimate key parameters for the vehicle. Field experiments in this thesis reveal that the proposed estimation structure is able to estimate the position, velocity, orientation, and longitudinal slip of the ARGO with a reasonable amount of accuracy. In addition, the proposed estimation structure is well-suited for online applications and can incorporate offline virtual GPS data to further improve the accuracy of the position estimates. The proposed estimation structure is also capable of estimating the longitudinal slip for every wheel of the ARGO, and the slip results align well with the motion estimate findings

Modeling and Improving Teleoperation Performance of Semi-Autonomous Wheeled Robots

Robotics and unmanned vehicles have allowed us to interact with environments in ways that were impossible decades ago. As perception, decision making, and control improve, it becomes possible to automate more parts of robot operation. However, humans will remain a critical part of robot control based on preference, ethical, and technical reasons. An ongoing question will be when and how to pair humans and automation to create semi-autonomous systems. The answer to this question depends on numerous factors such as the robot's task, platform, environment conditions, and the user. The work in this dissertation focuses on modeling the impact of these factors on performance and developing improved semi-autonomous control schemes, so that robot systems can be better designed. Experiments and analysis focus on wheeled robots, however the approach taken and many of the trends could be applied to a variety of platforms. Wheeled robots are often teleoperated over wireless communication networks. While this arrangement may be convenient, it introduces many challenges including time-varying delays and poor perception of the robot's environment that can lead to the robot colliding with objects or rolling over. With regards to semi-autonomous control, rollover prevention and obstacle avoidance behaviors are considered. In this area, two contributions are presented. The first is a rollover prevention method that uses an existing manipulator arm on-board a wheeled robot. The second is a method of approximating convex obstacle free regions for use in optimal control path planning problems. Teleoperation conditions, including communication delays, automation, and environment layout, are considered in modeling robot operation performance. From these considerations stem three contributions. The first is a method of relating driving performance among different communication delay distributions. The second parameterizes how driving through different arrangements of obstacles relates to performance. Lastly, based on user studies, teleoperation performance is related to different conditions of communication delay, automation level, and environment arrangement. The contributions of this dissertation will assist roboticists to implement better automation and understand when to use automation.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136951/1/jgstorms_1.pd

Development of a ground robot for indoor SLAM using Low‐Cost LiDAR and remote LabVIEW HMI

The simultaneous localization and mapping problem (SLAM) is crucial to autonomous navigation and robot mapping. The main purpose of this thesis is to develop a ground robot that implements SLAM to test the performance of the low‐cost RPLiDAR A1M8 by DFRobot. The HectorSLAM package, available in ROS was used with a Raspberry Pi to implement SLAM and build maps. These maps are sent to a remote desktop via TCP/IP communication to be displayed on a LabVIEW HMI where the user can also control robot. The LabVIEW HMI and the project in its entirety is intended to be as easy to use as possible to the layman, with many processes being automated to make this possible. The quality of the maps created by HectorSLAM and the RPLiDAR were evaluated both qualitatively and quanitatively to determine how useful the low‐cost LiDAR can be for this application. It is hoped that the apparatus developed in this project will be used with drones in the future for 3D mapping

ROS based Teleoperation and Docking of a Low Speed Urban Vehicle

In recent years, 4G LTE technology has provided us with higher than ever transfer speeds over the cellular networks, permitting streaming of video and other high bandwidth services. On the other hand, there has been a rapid development and an explosion of interest in frameworks for robot software development, particularly ROS. Though there have been many studies which have leveraged 4G LTE network as the mode of communication when studying teleoperations, a very few studies have used 4G LTE network with ROS framework for building teleoperated systems. Therefore, this study seeks to build a teleoperated system using the ROS framework which employs the 4G LTE network for communication. For this purpose, a prototype system is built using a remote-controlled low speed urban vehicle that hosts a multimedia link between the vehicle and the control station. The operator drives the vehicle remotely primarily based on processed video feed and LIDAR data. The vehicle is also equipped with safety systems to avoid collisions. The teleoperated system built is tested by asking an experienced driver to complete certain tasks while driving the vehicle remotely. Moreover, this study also intends to build an autonomous docking procedure for the vehicle. A docking procedure based on differential GPS and video feedback is built that allows the vehicle to autonomously dock itself into a charging station. The procedure provides a proof of concept solution for the autonomous charging/fueling of self-driving cars.  M.S

Reference Model for Interoperability of Autonomous Systems

This thesis proposes a reference model to describe the components of an Un-manned Air, Ground, Surface, or Underwater System (UxS), and the use of a single Interoperability Building Block to command, control, and get feedback from such vehicles. The importance and advantages of such a reference model, with a standard nomenclature and taxonomy, is shown. We overview the concepts of interoperability and some efforts to achieve common refer-ence models in other areas. We then present an overview of existing un-manned systems, their history, characteristics, classification, and missions. The concept of Interoperability Building Blocks (IBB) is introduced to describe standards, protocols, data models, and frameworks, and a large set of these are analyzed. A new and powerful reference model for UxS, named RAMP, is proposed, that describes the various components that a UxS may have. It is a hierarchical model with four levels, that describes the vehicle components, the datalink, and the ground segment. The reference model is validated by showing how it can be applied in various projects the author worked on. An example is given on how a single standard was capable of controlling a set of heterogeneous UAVs, USVs, and UGVs

Acceptance Testing and Energy-based Mission Reliability in Unmanned Ground Vehicles.

The objective of this research is to explore and develop new methodologies and techniques to improve UGV mission reliability. This dissertation focuses on two research issues that are critical in the following UGV deployment phases: (1) prior to field deployment to remove design deficiencies; and (2) during field usage to prevent mission failures. Four specific research topics are accomplished. The first topic focuses on simulation-based acceptance testing. A general framework is proposed to integrate dynamic and static simulations. Statistical hypothesis testing is used to compare static and dynamic simulations to determine when a simple static simulation can be used to replace the complex dynamic simulation. Results show that the static simulation can be used when a failure mechanism is not significantly affected by the dynamic characteristics of the vehicle. The remaining research topics aim at prevention of operational failures due to unexpected energy depletion. A model-based Bayesian prediction framework integrated with a dynamic vehicle model is proposed in the second research topic, which improves traditional approaches for estimation and prediction. The Bayesian framework combines mission prior knowledge with real-time measurements for adaptive prediction of end-of-mission energy requirement. Experimental studies were conducted, which validated and demonstrated the advantages of the framework on roads with different surface types and grades. The third research topic, entitled real-time energy reliable path planning, builds upon the above mentioned prediction framework to identify the most energy reliable path in a stochastic network with unknown and correlated arc lengths. Since traditional sequential optimization techniques cannot be directly applied to this problem, a heuristic approach based on two stage exploration/exploitation is proposed to identify the most reliable path. The framework, which minimizes the cost of exploration, outperforms traditional path planning approaches. In the final research topic, the impact of operator driving style on mission energy requirements is investigated using statistical response surface. While the previous topics help with overall mission planning regardless of the operator’s driving style, here, improving the driving style to increase energy availability is studied. The optimal drive cycle that minimizes energy consumption and procedures for reduction of energy consumption are proposed.PhDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107075/1/sadrpour_1.pd

Seventh Annual Workshop on Space Operations Applications and Research (SOAR 1993), volume 1

This document contains papers presented at the Space Operations, Applications and Research Symposium (SOAR) Symposium hosted by NASA/Johnson Space Center (JSC) on August 3-5, 1993, and held at JSC Gilruth Recreation Center. SOAR included NASA and USAF programmatic overview, plenary session, panel discussions, panel sessions, and exhibits. It invited technical papers in support of U.S. Army, U.S. Navy, Department of Energy, NASA, and USAF programs in the following areas: robotics and telepresence, automation and intelligent systems, human factors, life support, and space maintenance and servicing. SOAR was concerned with Government-sponsored research and development relevant to aerospace operations. More than 100 technical papers, 17 exhibits, a plenary session, several panel discussions, and several keynote speeches were included in SOAR '93