Sensor Fusion for Localization of Automated Guided Vehicles

Automated Guided Vehicles (AGVs) need to localize themselves reliably in order to perform their tasks efficiently. To that end, they rely on noisy sensor measurements that potentially provide erroneous location estimates if they are used directly. To prevent this issue, measurements from different kinds of sensors are generally used together. This thesis presents a Kalman Filter based sensor fusion approach that is able to function with asynchronous measurements from laser scanners, odometry and Inertial Measurement Units (IMUs). The method uses general kinematic equations for state prediction that work with any type of vehicle kinematics and utilizes state augmentation to estimate gyroscope and accelerometer biases. The developed algorithm was tested with an open source multisensor navigation dataset and real-time experiments with an AGV. In both sets of experiments, scenarios in which the laser scanner was fully available, partially available or not available were compared. It was found that using sensor fusion resulted in a smaller deviation from the actual trajectory compared to using only a laser scanner. Furthermore, in each experiment, using sensor fusion decreased the localization error in the time periods where the laser was unavailable, although the amount of improvement depended on the duration of unavailability and motion characteristic

From Flies to Robots: Inverted Landing in Small Quadcopters with Dynamic Perching

Inverted landing is a routine behavior among a number of animal fliers. However, mastering this feat poses a considerable challenge for robotic fliers, especially to perform dynamic perching with rapid body rotations (or flips) and landing against gravity. Inverted landing in flies have suggested that optical flow senses are closely linked to the precise triggering and control of body flips that lead to a variety of successful landing behaviors. Building upon this knowledge, we aimed to replicate the flies' landing behaviors in small quadcopters by developing a control policy general to arbitrary ceiling-approach conditions. First, we employed reinforcement learning in simulation to optimize discrete sensory-motor pairs across a broad spectrum of ceiling-approach velocities and directions. Next, we converted the sensory-motor pairs to a two-stage control policy in a continuous augmented-optical flow space. The control policy consists of a first-stage Flip-Trigger Policy, which employs a one-class support vector machine, and a second-stage Flip-Action Policy, implemented as a feed-forward neural network. To transfer the inverted-landing policy to physical systems, we utilized domain randomization and system identification techniques for a zero-shot sim-to-real transfer. As a result, we successfully achieved a range of robust inverted-landing behaviors in small quadcopters, emulating those observed in flies.Comment: 17 pages, 19 Figures, Journal paper currently under revie

人間を模擬した知覚系を持つ2足ヒューマノイドロボットの自己位置推定機能に対する歩行動作の影響に関する研究

早大学位記番号:新8279早稲田大

Utilisation de la poussée réversible pour faciliter les atterrissage de quadrirotors sur des surfaces inclinées

Les aéronefs télépilotés à voilure tournante, communément appelés multirotors, sont de plus en plus utilisé pour le loisir, mais aussi dans l'industrie. Leur fiabilité et leur performance ne cessent de s'accroître. Cependant, leur enveloppe d'atterrissage demeure limité. Effectivement, les multirotors commerciaux ne peuvent atterrir que des surfaces horizontales fixes. L'ajout de suspensions et de dispositifs d'adhérence spécialisés est nécessaire pour atterrir sur des surfaces inclinées. Le développement de rotors bidirectionnels, développés initialement pour des multirotors omnidirectionnels, pourrait améliorer l'atterrissage de ces aéronefs. En effet, en utilisant l'inversion de la poussée pour augmenter la force normale et la friction, il serait possible d'augmenter l'inclinaison maximale permettant un atterrissage sécuritaire et de diminuer l'espace requis pour l'atterrissage. Le projet de recherche présenté dans ce mémoire a pour but de quantifier les avantages de la poussée réversible ainsi que d'identifier les limites des bénéfices. Ce mémoire présente un modèle conçu pour simuler la dynamique d'un quadrirotor sujet aux contacts intermittents entre son train d'atterrissage et la surface, ainsi que la dynamique du rotor. Le modèle a été validé en effectuant des essais expérimentaux sur des surfaces à faible et à haute friction, et en utilisant des algorithmes génétiques pour identifier certains paramètres du modèle. À l'aide du modèle, plusieurs algorithmes simples d'atterrissage ont été simulés et puis testés expérimentalement. L'utilisation d'une impulsion angulaire à l'aide de la poussée différentielle afin d'éliminer la vitesse angulaire du quadrirotor après l'impact a aussi été étudiée. Finalement, les simulations et les essais démontrent que la poussée réversible peut presque doubler l'inclinaison maximale sur laquelle un quadrirotor peut atterrir ainsi que la vitesse verticale d'approche, tout en diminuant la distance et la durée requise pour l'atterrissage

Pedestrian localisation for indoor environments

Ubiquitous computing systems aim to assist us as we go about our daily lives, whilst at the same time fading into the background so that we do not notice their presence. To do this they need to be able to sense their surroundings and infer context about the state of the world. Location has proven to be an important source of contextual information for such systems. If a device can determine its own location then it can infer its surroundings and adapt accordingly. Of particular interest for many ubiquitous computing systems is the ability to track people in indoor environments. This interest has led to the development of many indoor location systems based on a range of technologies including infra-red light, ultrasound and radio. Unfortunately existing systems that achieve the kind of sub-metre accuracies desired by many location-aware applications require large amounts of infrastructure to be installed into the environment. This thesis investigates an alternative approach to indoor pedestrian tracking that uses on-body inertial sensors rather than relying on fixed infrastructure. It is demonstrated that general purpose inertial navigation algorithms are unsuitable for pedestrian tracking due to the rapid accumulation of errors in the tracked position. In practice it is necessary to frequently correct such algorithms using additional measurements or constraints. An extended Kalman filter is developed for this purpose and is applied to track pedestrians using foot-mounted inertial sensors. By detecting when the foot is stationary and applying zero velocity corrections a pedestrian’s relative movements can be tracked far more accurately than is possible using uncorrected inertial navigation. Having developed an effective means of calculating a pedestrian’s relative movements, a localisation filter is developed that combines relative movement measurements with environmental constraints derived from a map of the environment. By enforcing constraints such as impassable walls and floors the filter is able to narrow down the absolute position of a pedestrian as they move through an indoor environment. Once the user’s position has been uniquely determined the same filter is demonstrated to track the user’s absolute position to sub-metre accuracy. The localisation filter in its simplest form is computationally expensive. Furthermore symmetry exhibited by the environment may delay or prevent the filter from determining the user’s position. The final part of this thesis describes the concept of assisted localisation, in which additional measurements are used to solve both of these problems. The use of sparsely deployed WiFi access points is discussed in detail. The thesis concludes that inertial sensors can be used to track pedestrians in indoor environments. Such an approach is suited to cases in which it is impossible or impractical to install large amounts of fixed infrastructure into the environment in advance

Aerial Robotics for Inspection and Maintenance

Aerial robots with perception, navigation, and manipulation capabilities are extending the range of applications of drones, allowing the integration of different sensor devices and robotic manipulators to perform inspection and maintenance operations on infrastructures such as power lines, bridges, viaducts, or walls, involving typically physical interactions on flight. New research and technological challenges arise from applications demanding the benefits of aerial robots, particularly in outdoor environments. This book collects eleven papers from different research groups from Spain, Croatia, Italy, Japan, the USA, the Netherlands, and Denmark, focused on the design, development, and experimental validation of methods and technologies for inspection and maintenance using aerial robots

Inertial Motion Tracking for Inserting Humans into a Networked Synthetic Environment

Inertial/Magnetic tracking is based on the use of sensors containing three orthogonally mounted angular rate sensors, three orthogonal linear accelerometers and three orthogonal magnetometers to determine independently the orientation of each link of an articulated rigid body. Inertial/magnetic orientation tracking could be applied to a broad range of problems which require real-time tracking of an articulated structure without being continuously dependent upon an artificially generated source. This research focuses on the goal of developing and demonstrating wireless full body tracking using MARG sensor modules.U.S. Army Research OfficeW911NF-04-1-030

Development of a Two-Wheel Inverted Pendulum and a Cable Climbing Robot

The research work in this thesis constitutes two parts: one is the development and control of a Two-wheel inverted pendulum (TWIP) robot and the other is the design and manufacturing of a cable climbing robot (CCR) for suspension bridge inspection. The first part of this research investigates a sliding mode controller for self-balancing and stabilizing a two-wheel inverted pendulum (TWIP) robot. The TWIP robot is constructed by using two DC gear motors with a high-resolution encoder and zero backlashes, but with friction. It is a highly nonlinear and unstable system, which poses challenges for controller design. In this study, a dynamic mathematical model is built using the Lagrangian function method. And a sliding mode controller (SMC) is proposed for auto-balancing and yaw rotation. A gyro and an accelerometer are adopted to measure the pitch angle and pitch rate. The effect on the sensor’s installation location is analyzed and compensated, and the precision of the pose estimation is improved accordingly. A comparison of the proposed SMC controller with a proportional-integral-derivative (PID) controller and state feedback controller (SFC) with linear quadratic regulation (LQR) has been conducted. The simulation and experimental test results demonstrate the SMC controller outperforms the PID controller and SFC in terms of transient performance and disturbance rejection ability. In the second part of the research, a wheel-based cable climbing robotic system which can climb up and down the cylindrical cables for the inspection of the suspension bridges is designed and manufactured. Firstly, a rubber track climbing mechanism is designed to generate enough adhesion force for the robot to stick to the surface of a cable and the driving force for the robot to climb up and down the cable, while not too big to damage the cable. The climbing system includes chains and sprockets driven by the DC motors and adhesion system. The unique design of the adhesion mechanism lies in that it can maintain the adhesion force even when the power is lost while the system works as a suspension mechanism. Finally, a safe-landing mechanism is developed to guarantee the safety of the robot during inspection operations on cables. The robot has been fully tested in the inspection of Xili bridge, Guangzhou, P.R. China

Design, construction and flight control of a quad tilt-wing unmanned aerial vehicle

Unmanned Aerial Vehicles (UAVs) are flying robots that are employed both in civilian and military applications with a steeply increasing trend. They are already used extensively in civilian applications such as law enforcement, earth surface mapping and surveillance in disasters, and in military missions such as surveillance, reconnaissance and target acquisition. As the demand on their utilization increases, novel designs with far more advances in autonomy, flight capabilities and payloads for carrying more complex and intelligent sensors are emerging. With these technological advances, people will find even newer operational fields for UAVs. This thesis work focuses on the design, construction and flight control of a novel UAV (SUAVI: Sabanci University Unmanned Aerial VehIcle). SUAVI is an electric powered compact size quad tilt-wing UAV, which is capable of vertical takeoff and landing (VTOL) like a helicopter, and flying horizontally like an airplane by tilting its wings. It carries onboard cameras for capturing images and broadcasting them via RF communication with the ground station. In the aerodynamic and mechanical design of SUAVI, flight duration, flight speed, size, power source and missions to be carried out are taken into account. The aerodynamic design is carried out by considering the maximization of the aerodynamic efficiency and the safe fiight characteristics. The components in the propulsion system are selected to optimize propulsion efficiency and fulfill the requirements of the control for a stable flight in the entire speed range. Simulation results obtained by ANSYS and NASA FoilSimII are evaluated and motor thrust tests are conducted during this optimization process. The power source is determined by taking the weight and flight duration into account. The wings and the fuselage are shaped iteratively in fluid flow simulations. Additionally, the verification of aerodynamic design and maneuverability are assessed in the wind tunnel tests on the half-body prototype. The mechanical structure is designed to be lightweight, strong and protective, and to allow easy assembly and disassembly of SUAVI for practical use. The safety factors in the mechanical system are determined using FEM analysis in ANSYS environment. Specimens of candidate composite skin materials are prepared and tested for lightness, strength and integrity in mechanical tests. The ready for flight prototype SUAVI is produced from the selected composite material. Dynamical model of SUAVI is obtained using Newton-Euler formulation. Aerodynamic disturbances such as wind gusts are modeled using the wellknown Dryden wind turbulence model. As the flight control system, a supervisory control architecture is implemented where a Gumstix microcomputer and several Atmega16 microcontrollers are used as the high-level and low- level controllers, respectively. Gumstix computer acts as a supervisor which orchestrates switching of low-level controllers into the system and is responsible for decision making, monitoring states of the vehicle and safety checks during the entire flight. It also generates attitude references for the low-level controllers using data from GPS or camera. Various analog and digital filters are implemented to smooth out noisy sensor measurements. Extended Kalman filter is utilized to obtain reliable orientation information by fusing data from low-cost MEMS inertial sensors such as gyros, accelerometers and the compass. PID controllers are implemented for both the high-level GPS based acceleration controller and the low-level altitude and attitude controllers. External disturbances are estimated and compensated by a disturbance observer. Real-time control software is developed for the whole fiight control system. SUAVI can operate in semi-autonomous mode by communicating with the ground station. A quadrotor test platform (SUQUAD: Sabanci University QUADrotor) is also produced and used for the initial performance tests of the fiight control system. After successful fiight tests on this platform, the control system is transferred to SUAVI. Performance of the flight control system is verified by numerous simulations and real flight experiments. VTOL and horizontal flights are successfully realized

Environment Search Planning Subject to High Robot Localization Uncertainty

As robots find applications in more complex roles, ranging from search and rescue to healthcare and services, they must be robust to greater levels of localization uncertainty and uncertainty about their environments. Without consideration for such uncertainties, robots will not be able to compensate accordingly, potentially leading to mission failure or injury to bystanders. This work addresses the task of searching a 2D area while reducing localization uncertainty. Wherein, the environment provides low uncertainty pose updates from beacons with a short range, covering only part of the environment. Otherwise the robot localizes using dead reckoning, relying on wheel encoder and yaw rate information from a gyroscope. As such, outside of the regions with position updates, there will be unconstrained localization error growth over time. The work contributes a Belief Markov Decision Process formulation for solving the search problem and evaluates the performance using Partially Observable Monte Carlo Planning (POMCP). Additionally, the work contributes an approximate Markov Decision Process formulation and reduced complexity state representation. The approximate problem is evaluated using value iteration. To provide a baseline, the Google OR-Tools package is used to solve the travelling salesman problem (TSP). Results are verified by simulating a differential drive robot in the Gazebo simulation environment. POMCP results indicate planning can be tuned to prioritize constraining uncertainty at the cost of increasing path length. The MDP formulation provides consistently lower uncertainty with minimal increases in path length over the TSP solution. Both formulations show improved coverage outcomes