A Novel Robotic Surveying Technique for Free-Falling Penetrometers

Severe floods and sea level rise (SLR) are increasingly urgent effects of global climate change. Wetlands are natural buffers that prevent inundation and destruction from floods. Anthropogenic destruction of wetlands is reducing their effectiveness as flood buffers. Rapid and timely assessment methods are needed for the effective restoration of the wetlands. This thesis presents a novel method for performing free falling penetrometer (FFP) tests for soft wetland soils. The method involves the aerial deployment of a custom FFP using a consumer quadcopter. The method was tested in three soils to examine the effect of drop height on the FFP deceleration profile and penetration depth. Further tests were conducted to determine the force required to extract the FFP after a successful drop. The effects of speed and angle on extraction force was analyzed. Field tests were simulated by conducting limited indoor surveys with the FFP and a consumer drone. The custom FFP was successful in distinguishing wetland soils in drop experiments. The relationships between drop height, penetration depth and deceleration profile were characterized. Data from extraction tests revealed a linear relationship between extraction force and speed; and an inverse relationship between extraction force and angle. By utilizing techniques to minimize the extraction force, a consumer drone was successful in deploying and retrieving the custom FFP. Further field tests are needed to validate the robustness of the novel method. If proven reliable, this method will be useful in reducing the financial and labor costs associated with wetlands surveys.Mechanical Engineering, Department ofHonors Colleg

Dense and long-term monitoring of Earth surface processes with passive RFID -- a review

Billions of Radio-Frequency Identification (RFID) passive tags are produced yearly to identify goods remotely. New research and business applications are continuously arising, including recently localization and sensing to monitor earth surface processes. Indeed, passive tags can cost 10 to 100 times less than wireless sensors networks and require little maintenance, facilitating years-long monitoring with ten's to thousands of tags. This study reviews the existing and potential applications of RFID in geosciences. The most mature application today is the study of coarse sediment transport in rivers or coastal environments, using tags placed into pebbles. More recently, tag localization was used to monitor landslide displacement, with a centimetric accuracy. Sensing tags were used to detect a displacement threshold on unstable rocks, to monitor the soil moisture or temperature, and to monitor the snowpack temperature and snow water equivalent. RFID sensors, available today, could monitor other parameters, such as the vibration of structures, the tilt of unstable boulders, the strain of a material, or the salinity of water. Key challenges for using RFID monitoring more broadly in geosciences include the use of ground and aerial vehicles to collect data or localize tags, the increase in reading range and duration, the ability to use tags placed under ground, snow, water or vegetation, and the optimization of economical and environmental cost. As a pattern, passive RFID could fill a gap between wireless sensor networks and manual measurements, to collect data efficiently over large areas, during several years, at high spatial density and moderate cost.Comment: Invited paper for Earth Science Reviews. 50 pages without references. 31 figures. 8 table

A Heterogeneous Robotics Team for Large-Scale Seismic Sensing

Seismic surveying requires placing a large number of sensors (geophones) in a grid pattern, triggering a seismic event, and recording vibration readings. The goal of the surveying is often to locate subsurface resources. Traditional seismic surveying employs human laborers for sensor placement and retrieval. The major drawbacks of surveying with human deployment are the high costs and time, and risks to humans due to explosives, terrain, and climatic conditions. We propose an autonomous, heterogeneous sensor deployment system using unmanned aerial vehicles to deploy mobile and immobile sensors. The proposed system begins to overcome some of the problems associated with traditional systems. This paper provides detailed analysis and comparison with traditional survey techniques. Hardware experiments and simulations show promise for automation reducing cost and time. Autonomous aerial systems will have a substantial contribution to make in future seismic surveys

Vision-Based Control of Unmanned Aerial Vehicles for Automated Structural Monitoring and Geo-Structural Analysis of Civil Infrastructure Systems

The emergence of wireless sensors capable of sensing, embedded computing, and wireless communication has provided an affordable means of monitoring large-scale civil infrastructure systems with ease. To date, the majority of the existing monitoring systems, including those based on wireless sensors, are stationary with measurement nodes installed without an intention for relocation later. Many monitoring applications involving structural and geotechnical systems require a high density of sensors to provide sufficient spatial resolution to their assessment of system performance. While wireless sensors have made high density monitoring systems possible, an alternative approach would be to empower the mobility of the sensors themselves to transform wireless sensor networks (WSNs) into mobile sensor networks (MSNs). In doing so, many benefits would be derived including reducing the total number of sensors needed while introducing the ability to learn from the data obtained to improve the location of sensors installed. One approach to achieving MSNs is to integrate the use of unmanned aerial vehicles (UAVs) into the monitoring application. UAV-based MSNs have the potential to transform current monitoring practices by improving the speed and quality of data collected while reducing overall system costs. The efforts of this study have been chiefly focused upon using autonomous UAVs to deploy, operate, and reconfigure MSNs in a fully autonomous manner for field monitoring of civil infrastructure systems. This study aims to overcome two main challenges pertaining to UAV-enabled wireless monitoring: the need for high-precision localization methods for outdoor UAV navigation and facilitating modes of direct interaction between UAVs and their built or natural environments. A vision-aided UAV positioning algorithm is first introduced to augment traditional inertial sensing techniques to enhance the ability of UAVs to accurately localize themselves in a civil infrastructure system for placement of wireless sensors. Multi-resolution fiducial markers indicating sensor placement locations are applied to the surface of a structure, serving as navigation guides and precision landing targets for a UAV carrying a wireless sensor. Visual-inertial fusion is implemented via a discrete-time Kalman filter to further increase the robustness of the relative position estimation algorithm resulting in localization accuracies of 10 cm or smaller. The precision landing of UAVs that allows the MSN topology change is validated on a simple beam with the UAV-based MSN collecting ambient response data for extraction of global mode shapes of the structure. The work also explores the integration of a magnetic gripper with a UAV to drop defined weights from an elevation to provide a high energy seismic source for MSNs engaged in seismic monitoring applications. Leveraging tailored visual detection and precise position control techniques for UAVs, the work illustrates the ability of UAVs to—in a repeated and autonomous fashion—deploy wireless geophones and to introduce an impulsive seismic source for in situ shear wave velocity profiling using the spectral analysis of surface waves (SASW) method. The dispersion curve of the shear wave profile of the geotechnical system is shown nearly equal between the autonomous UAV-based MSN architecture and that taken by a traditional wired and manually operated SASW data collection system. The developments and proof-of-concept systems advanced in this study will extend the body of knowledge of robot-deployed MSN with the hope of extending the capabilities of monitoring systems while eradicating the need for human interventions in their design and use.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169980/1/zhh_1.pd