Planning in information space for a quadrotor helicopter in a GPS-denied environment

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008.Includes bibliographical references (leaves 85-87).Unmanned Air Vehicles (UAVs) have thus far had limited success in flying autonomously indoors, with the exception of specially instrumented locations. In indoor environments, accurate global positioning information is unavailable, and the vehicle has to rely on onboard sensors to detect environmental features and infer its position. Given that a vehicle small enough to fly indoors can only carry a limited sensor payload, the vehicle's ability to localize itself varies across different environments, since different surroundings provide varying degrees of sensor information. Therefore, a vehicle that plans a path without regard to how well it can localize itself along that path runs the risk of becoming lost. My research focuses on how path-planning can be performed to minimize localization uncertainty, and works towards developing a motion-planning algorithm for a quadrotor helicopter. As a starting point, I apply the Belief Roadmap (BRM) algorithm, an information-theoretic extension of the Probabilistic Roadmap algorithm, incorporating sensing during the path-planning process. I make two theoretical contributions in this research. First, I extend the original BRM to use non-linear state inference via the Unscented Kalman Filter, providing better approximation of the non-linearities of laser sensing onboard the UAV. Second, I develop a sampling strategy for the BRM, minimizing the number of samples required to find a good path. Finally, I demonstrate the BRM path-planning algorithm on a quadrotor helicopter, navigating the vehicle autonomously in an indoor environment.by Ruijie He.S.M

Comparative Study of Indoor Navigation Systems for Autonomous Flight

Recently, Unmanned Aerial Vehicles (UAVs) have attracted the society and researchers due to the capability to perform in economic, scientific and emergency scenarios, and are being employed in large number of applications especially during the hostile environments. They can operate autonomously for both indoor and outdoor applications mainly including search and rescue, manufacturing, forest fire tracking, remote sensing etc. For both environments, precise localization plays a critical role in order to achieve high performance flight and interacting with the surrounding objects. However, for indoor areas with degraded or denied Global Navigation Satellite System (GNSS) situation, it becomes challenging to control UAV autonomously especially where obstacles are unidentified. A large number of techniques by using various technologies are proposed to get rid of these limits. This paper provides a comparison of such existing solutions and technologies available for this purpose with their strengths and limitations. Further, a summary of current research status with unresolved issues and opportunities is provided that would provide research directions to the researchers of the similar interests

Control and planning for vehicles with uncertainty in dynamics

Abstract-This paper describes a motion planning algorithm that accounts for uncertainty in the dynamics of vehicles. This noise is a function of the type of controller employed on the vehicle and the characteristics of the terrain and can cause the robot to deviate from a planned trajectory and collide with obstacles. Our motion planning algorithm finds trajectories that balance the trade-off between conventional performance measures such as time and energy versus safety. The key is a characterization of the vehicle's ability to follow planned paths, which allows the algorithm to explicitly calculate probabilities of successful traversal for different trajectory segments. We illustrate the method with a six-legged Rhex-like robot by experimentally characterizing different gaits (controllers) on different terrains and demonstrating the hexapod navigating a multi-terrain environment

Quadrotor control for persistent surveillance of dynamic environments

Thesis (M.S.)--Boston UniversityThe last decade has witnessed many advances in the field of small scale unmanned aerial vehicles (UAVs). In particular, the quadrotor has attracted significant attention. Due to its ability to perform vertical takeoff and landing, and to operate in cluttered spaces, the quadrotor is utilized in numerous practical applications, such as reconnaissance and information gathering in unsafe or otherwise unreachable environments. This work considers the application of aerial surveillance over a city-like environment. The thesis presents a framework for automatic deployment of quadrotors to monitor and react to dynamically changing events. The framework has a hierarchical structure. At the top level, the UAVs perform complex behaviors that satisfy high- level mission specifications. At the bottom level, low-level controllers drive actuators on vehicles to perform the desired maneuvers. In parallel with the development of controllers, this work covers the implementation of the system into an experimental testbed. The testbed emulates a city using physical objects to represent static features and projectors to display dynamic events occurring on the ground as seen by an aerial vehicle. The experimental platform features a motion capture system that provides position data for UAVs and physical features of the environment, allowing for precise, closed-loop control of the vehicles. Experimental runs in the testbed are used to validate the effectiveness of the developed control strategies

Fast, Autonomous Flight in GPS-Denied and Cluttered Environments

One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment. This challenge is addressed in the present paper. We describe the system design and software architecture of our proposed solution, and showcase how all the distinct components can be integrated to enable smooth robot operation. We provide critical insight on hardware and software component selection and development, and present results from extensive experimental testing in real-world warehouse environments. Experimental testing reveals that our proposed solution can deliver fast and robust aerial robot autonomous navigation in cluttered, GPS-denied environments.Comment: Pre-peer reviewed version of the article accepted in Journal of Field Robotic