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Title

EVALUATING INTEGRITY FOR MOBILE ROBOT LOCALIZATION SAFETY

Creator

Duenas Arana, Guillermo

Date

2019

Description

Precise localization is paramount for autonomous navigation. Localization errors are not only dangerous by themselves, but can also mislead...
Show morePrecise localization is paramount for autonomous navigation. Localization errors are not only dangerous by themselves, but can also mislead other dependent systems into moving to a hazardous location. Unfortunately, the problem of quantifying robot localization safety is only sparsely addressed in the robotics literature, and most robotics algorithms still quantify pose estimation performance using a covariance matrix or particle spread, which only accounts for nominal sensor errors. This is insufficient for life- and mission-critical applications, such as autonomous vehicles and other co-robots, where ignoring sensor or sensor or processing faults can lead to catastrophic localization errors. Thus, other methods must be employed to ensure safety.In response, this research leverages prior work in aviation integrity monitoring to tackle the more challenging case of evaluating localization safety in mobile robots. In contrast to aviation applications, that heavily rely on the Global Navigation Satellite System (GNSS) for localization, robots often operate in complex, GNSS-denied environments that require a more sophisticated sensor suite to ensure localization safety. Localization integrity risk is the probability that a robot's pose estimate lies outside pre-defined acceptable limits while no alarm is triggered. In this work, the integrity risk is rigorously upper bounded by accounting for both nominal noise and other non-nominal sensor faults, resulting in a safe upper bound on the localization integrity risk.The main contribution of this dissertation is the design and evaluation of a sequential integrity monitoring methodology applicable to mobile robot localization algorithms that use feature extraction and data association. First, faults introduced during the feature extraction and data association processes are distinguished, and the probability of the latter is rigorously upper bounded using analytical methods. The impact of faults in the estimate error's and fault detector's distributions is then determined to quantify integrity risk, which is evaluated under the worst-possible fault combination. To determine the impact of previous faults without a boundlessly growing number of fault hypotheses, this dissertation presents a novel method that uses a preceding time window to build a limited set of hypotheses and a prior estimate bias to account for faults occurring before the start of the time window. The proposed methodology is applicable to Kalman Filter and fixed-lag smoothing localization. Simulated and experimental results are presented to validate the methodology.
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Title

Modeling and Control Methods for Boundary Constrained Soft Robots

Creator

Zhou, Qiyuan

Date

2021

Description

Soft and deformable robots have been an active field of research in the past few years. However, they are limited in that they cannot apply...
Show moreSoft and deformable robots have been an active field of research in the past few years. However, they are limited in that they cannot apply much force to an environment due to the limitations of the flexible materials from which they are made of. To help overcome this limitation, a new architecture named the Jamming and Morphing Enabled Bot Array (JAMoEBA) system was conceived. This system consists of a flexible outer membrane which encloses an interior composed of a granular medium. Active sub-units along the flexible outer membrane allow for actuation and locomotion of the system. The granular material coupled with the flexible outer membrane allows the robot to maintain the characteristics typically associated with soft robots (continuum, compliant, configurable). At the same time, the granular material is also able to undergo a solid phase transition with the application of pressure to the flexible outer membrane and allow the system to behave more like a rigid robot if needed. This allows for the robot system to exploit the desirable characteristics of both soft and rigid robots in its tasks.The purpose of this thesis is to offer a discussion and demonstration of various simulation methods for the physically accurate modeling of the JAMoEBA constrained boundary robotic system and to show some of the control methods which have been investigated within the selected modeling framework. Simulation methods based on Lennard-Jones (L-J) potentials, non-smooth contact dynamics (NSCD), as well as the discrete element methods based on complementarity (DEM-C) and penalty (DEM-P) conditions as implemented in the open source physics library Project Chrono are considered. Comparisons are made in the areas of physical accuracy, computational efficiency, and feature availability in the consideration of the best simulation method for the JAMoEBA system. Investigations of control strategies such as leader-follower and heuristics based approaches are carried out using the selected simulation method. Finally, a framework for self contained localization which relies on measurements from onboard sensors and linear Kalman filtering is tested within the simulation framework, and the effectiveness of approximating the shape of the JAMoEBA system using elliptical Fourier descriptors is shown.The main contributions made in this thesis are in the areas of suitable modeling methods, controls strategies, and localization techniques for the novel boundary constrained JAMoEBA soft robot architecture. The work done serves as a solid foundation for the future study of this novel soft robotic architecture due to the demonstration of successful methods for modeling, control, and localization of the system. The work presented is not meant to be a comprehensive or deep dive into any one specific area, but rather a jumping off point for future areas of research.
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