Robot navigation in dense crowds : statistical models and experimental studies of human robot cooperation

This thesis explores the problem of mobile robot navigation in dense human crowds. We begin by considering a fundamental impediment to classical motion planning algorithms called the freezing robot problem: once the environment surpasses a certain level of complexity, the planner decides that all forward paths are unsafe, and the robot freezes in place (or performs unnecessary maneuvers) to avoid collisions. Since a feasible path typically exists, this behavior is suboptimal. Existing approaches have focused on reducing predictive uncertainty by employing higher fidelity individual dynamics models or heuristically limiting the individual predictive covariance to prevent overcautious navigation. We demonstrate that both the individual prediction and the individual predictive uncertainty have little to do with this undesirable navigation behavior. Additionally, we provide evidence that dynamic agents are able to navigate in dense crowds by engaging in joint collision avoidance, cooperatively making room to create feasible trajectories. We accordingly develop interacting Gaussian processes, a prediction density that captures cooperative collision avoidance, and a "multiple goal" extension that models the goal driven nature of human decision making. Navigation naturally emerges as a statistic of this distribution.

Most importantly, we empirically validate our models in the Chandler dining hall at Caltech during peak hours, and in the process, carry out the first extensive quantitative study of robot navigation in dense human crowds (collecting data on 488 runs). The multiple goal interacting Gaussian processes algorithm performs comparably with human teleoperators in crowd densities nearing 1 person/m², while a state of the art noncooperative planner exhibits unsafe behavior more than 3 times as often as the multiple goal extension, and twice as often as the basic interacting Gaussian process approach. Furthermore, a reactive planner based on the widely used dynamic window approach proves insufficient for crowd densities above 0.55 people/m². We also show that our noncooperative planner or our reactive planner capture the salient characteristics of nearly any dynamic navigation algorithm. For inclusive validation purposes, we show that either our non-interacting planner or our reactive planner captures the salient characteristics of nearly any existing dynamic navigation algorithm. Based on these experimental results and theoretical observations, we conclude that a cooperation model is critical for safe and efficient robot navigation in dense human crowds.

Finally, we produce a large database of ground truth pedestrian crowd data. We make this ground truth database publicly available for further scientific study of crowd prediction models, learning from demonstration algorithms, and human robot interaction models in general.

Using space geodesy to constrain variations in seismogenic behavior on subduction megathrusts

The concept of seismogenic asperities and aseismic barriers has become a useful paradigm within which to understand the seismogenic behavior of major faults. Since asperities and barriers can be thought of as defining the potential rupture area of large megathrust earthquakes, it is thus important to identify their respective spatial extents, constrain their temporal longevity, and to develop a physical understanding for their behavior. Space geodesy is making critical contributions to the identification of slip asperities and barriers but progress in many geographical regions depends on improving the accuracy and precision of the basic measurements. This thesis begins with technical developments aimed at improving satellite radar interferometric measurements of ground deformation whereby we introduce an empirical correction algorithm for unwanted effects due to interferometric path delays that are due to spatially and temporally variable radar wave propagation speeds in the atmosphere. In chapter 2, I combine geodetic datasets with complementary spatio-temporal resolutions to improve our understanding of the spatial distribution of crustal deformation sources and their associated temporal evolution – here we use observations from Long Valley Caldera (California) as our test bed. In the third chapter I apply the tools developed in the first two chapters to analyze postseismic deformation associated with the 2010 Mw=8.8 Maule (Chile) earthquake. The result delimits patches where afterslip occurs, explores their relationship to coseismic rupture, quantifies frictional properties associated with inferred patches of afterslip, and discusses the relationship of asperities and barriers to long-term topography. The final chapter investigates interseismic deformation of the eastern Makran subduction zone by using satellite radar interferometry only, and demonstrates that with state-of-art techniques it is possible to quantify tectonic signals with small amplitude and long wavelength. Portions of the eastern Makran for which we estimate low fault coupling correspond to areas where bathymetric features on the downgoing plate are presently subducting, whereas the region of the 1945 M=8.1 earthquake appears to be more highly coupled.

Radar methods for the exploration of glaciers

The problem of finding the depths of glaciers and the current methods are discussed briefly. Radar methods are suggested as a possible improvement for, or adjunct to, seismic and gravity survey methods. The feasibility of propagating electromagnetic waves in ice and the maximum range to be expected are then investigated theoretically with the aid of experimental data on the dielectric properties of ice. It is found that the maximum expected range is great enough to measure the depth of many glaciers at the lower radar frequencies if there is not too much liquid water present. Greater ranges can be attained by going to lower frequencies.

The results are given of two expeditions in two different years to the Seward Glacier in the Yukon Territory. Experiments were conducted on a small valley glacier whose depth was determined by seismic sounding. Many echoes were received but their identification was uncertain. Using the best echoes, a profile was obtained each year, but they were not in exact agreement with each other. It could not be definitely established that echoes had been received from bedrock. Agreement with seismic methods for a considerable number of glaciers would have to be obtained before radar methods could be relied upon. The presence of liquid water in the ice is believed to be one of the greatest obstacles. Besides increasing the attenuation and possibly reflecting energy, it makes it impossible to predict the velocity of propagation. The equipment used was far from adequate for such purposes, so many of the difficulties could be attributed to this. Partly because of this, and the fact that there are glaciers with very little liquid water present, radar methods are believed to be worthy of further research for the exploration of glaciers.