skip to main content

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: A CAMERA AND RANGE SENSOR FUSION APPROACH FOR AUTONOMOUS NAVIGATION SYSTEMS DRIVEN BY ROBUST ADAPTIVE CONTROL
An integrated sensing approach that fuses vision and range information to land an autonomous class 1 unmanned aerial system (UAS) controlled by e-modification model reference adaptive control is presented. The navigation system uses a feature detection algorithm to locate features and compute the corresponding range vectors on a coarsely instrumented landing platform. The relative translation and rotation state is estimated and sent to the flight computer for control feedback. A robust adaptive control law that guarantees uniform ultimate boundedness of the adaptive gains in the presence of bounded external disturbances is used to control the flight vehicle. Experimental flight tests are conducted to validate the integration of these systems and measure the quality of result from the navigation solution. Robustness of the control law amidst flight disturbances and hardware failures is demonstrated. The research results demonstrate the utility of low-cost, low-weight navigation solutions for navigation of small, autonomous UAS to carryout littoral proximity operations about unprepared shipdecks.  more » « less
Award ID(s):
1946890
PAR ID:
10318617
Author(s) / Creator(s):
Date Published:
Journal Name:
44th annual AAS Guidance, Navigation and Control Conference
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ( , Frontiers in Neuroscience)
    null (Ed.)
    Autonomous flight for large aircraft appears to be within our reach. However, launching autonomous systems for everyday missions still requires an immense interdisciplinary research effort supported by pointed policies and funding. We believe that concerted endeavors in the fields of neuroscience, mathematics, sensor physics, robotics, and computer science are needed to address remaining crucial scientific challenges. In this paper, we argue for a bio-inspired approach to solve autonomous flying challenges, outline the frontier of sensing, data processing, and flight control within a neuromorphic paradigm, and chart directions of research needed to achieve operational capabilities comparable to those we observe in nature. One central problem of neuromorphic computing is learning. In biological systems, learning is achieved by adaptive and relativistic information acquisition characterized by near-continuous information retrieval with variable rates and sparsity. This results in both energy and computational resource savings being an inspiration for autonomous systems. We consider pertinent features of insect, bat and bird flight behavior as examples to address various vital aspects of autonomous flight. Insects exhibit sophisticated flight dynamics with comparatively reduced complexity of the brain. They represent excellent objects for the study of navigation and flight control. Bats and birds enable more complex models of attention and point to the importance of active sensing for conducting more complex missions. The implementation of neuromorphic paradigms for autonomous flight will require fundamental changes in both traditional hardware and software. We provide recommendations for sensor hardware and processing algorithm development to enable energy efficient and computationally effective flight control. 
    more » « less
  2. ; ; ; ( , 2022 ASEE Annual Conference & Exposition)
    Designing a senior-level course that involves problem-based learning, including project completion task, is laborious and challenging. A well-designed project motivates the students to be self-learners and prepares them for future industrial or academic endeavors. The COVID-19 pandemic brought many challenges when instructions were forced to move either online or to a remote teaching/learning environment. Due to this rapid transition, delivery modes in teaching and learning modalities faced disruption making course design more difficult. The senior level Flight Controls course AME - 4513 is designed with Unmanned Aerial Systems (UAS) related projects for the students to have a better understanding of UAS usage on various applications in support of Advanced Technological Education (ATE) program. The purpose of this paper is to present the UAS lab modules in a junior level robotics lab, AME - 4802, which preceded the Flight Controls course in the school of Aerospace and Mechanical Engineering at the University of Oklahoma. Successfully completing the course project requires independent research and involves numerical simulations of UAS. The Robotics Lab course focuses on hands-on projects of robotic systems with an emphasis on semi-autonomous mobile robots, including an UAS introduction module. - The UAS module in the Robotics Lab class is introduced in Spring 2020. Therefore, most of the students enrolled in the Spring 2020 Robotics Lab course have introductory knowledge about the UAS system when taking the Fall 2020 Flight Control course. In addition, Spring 2020 Robotics Lab was affected due to COVID-19. - The UAS module was not introduced in 2019 Spring Robotics lab. Thus, the students enrolled in Fall 2019 Flight Controls course did not have prior knowledge on the UAS system. - We thus present the implementation of UAS module in a junior level robotics lab which preceded the senior level Flight Controls course in following Fall semester, when the same instructor taught the course. 
    more » « less
  3. ; ; ( , 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC))
    Unmanned aircraft systems (UAS) are being used more and more every day in almost any area to solve challenging real-life problems. Increased autonomy and advancements in low-cost high-computing technologies made these compact autonomous solutions accessible to any party with ease. However, this ease of use brings its own challenges that need to be addressed. In an autonomous flight scenario over a public space, an autonomous operation plan has to consider the public safety and regulations as well as the task specific objectives. In this work, we propose a generic utility function for the path planning of UAS operations that includes the benefits of accomplishing the goals as well as the safety risks incurred along the flight trajectories, with the purpose of making task-level decisions through the optimization of the carefully constructed utility function for a given scenario. As an optimizer, we benefited from a multi-tree variant of the optimal T-RRT * (Multi-T-RRT * path planning algorithm. To illustrate its operation, results of simulation of a UAS scenario are presented. 
    more » « less
  4. ; ; ; ; ( , 2021 IEEE International Conference on Robotics and Automation)
    null (Ed.)
    This work presents the design and autonomous navigation policy of the Resilient Micro Flyer, a new type of collision-tolerant robot tailored to fly through extremely confined environments and manhole-sized tubes. The robot maintains a low weight (<500g) and implements a combined rigid-compliant design through the integration of elastic flaps around its stiff collision-tolerant frame. These passive flaps ensure compliant collisions, contact sensing and smooth navigation in contact with the environment. Focusing on resilient autonomy, capable of running on resource-constrained hardware, we demonstrate the beneficial role of compliant collisions for the reliability of the onboard visual-inertial odometry and propose a safe navigation policy that exploits both collision-avoidance using lightweight time-of-flight sensing and adaptive control in response to collisions. The robot further realizes an explicit manhole navigation mode that exploits the direct mechanical feedback provided by the flaps and a special navigation strategy to self-align inside manholes with non-straight geometry. Comprehensive experimental studies are presented to evaluate, both individually and as a whole, how resilience is achieved based on the robot design and its navigation scheme. 
    more » « less
  5. ; ( , 2018 IEEE Intelligent Vehicles Symposium (IV))
    Urban environments offer a challenging scenario for autonomous driving. Globally localizing information, such as a GPS signal, can be unreliable due to signal shadowing and multipath errors. Detailed a priori maps of the environment with sufficient information for autonomous navigation typically require driving the area multiple times to collect large amounts of data, substantial post-processing on that data to obtain the map, and then maintaining updates on the map as the environment changes. This paper addresses the issue of autonomous driving in an urban environment by investigating algorithms and an architecture to enable fully functional autonomous driving with limited information. An algorithm to autonomously navigate urban roadways with little to no reliance on an a priori map or GPS is developed. Localization is performed with an extended Kalman filter with odometry, compass, and sparse landmark measure ment updates. Navigation is accomplished by a compass-based navigation control law. Key results from Monte Carlo studies show success rates of urban navigation under different environmental conditions. Experiments validate the simulated results and demonstrate that, for given test conditions, an expected range can be found for a given success rate. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email