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Now showing 1 - 10 of 1100
  • Publication
    Machine Learning For Robot Motion Planning
    (2021-01-01) Zhang, Clark June
    Robot motion planning is a field that encompasses many different problems and algorithms. From the traditional piano mover's problem to more complicated kinodynamic planning problems, motion planning requires a broad breadth of human expertise and time to design well functioning algorithms. A traditional motion planning pipeline consists of modeling a system and then designing a planner and planning heuristics. Each part of this pipeline can incorporate machine learning. Planners and planning heuristics can benefit from machine learned heuristics, while system modeling can benefit from model learning. Each aspect of the motion planning pipeline comes with trade offs between computational effort and human effort. This work explores algorithms that allow motion planning algorithms and frameworks to find a compromise between the two. First, a framework for learning heuristics for sampling-based planners is presented. The efficacy of the framework depends on human designed features and policy architecture. Next, a framework for learning system models is presented that incorporates human knowledge as constraints. The amount of human effort can be modulated by the quality of the constraints given. Lastly, semi-automatic constraint generation is explored to enable a larger range of trade-offs between human expert constraint generation and data driven constraint generation. We apply these techniques and show results in a variety of robotic systems.
  • Publication
    Computer-Aided Clinical Trials For Medical Devices
    (2021-01-01) Jang, Kuk Jin
    Life-critical medical devices require robust safety and efficacy to treat patient populations with potentially large patient heterogeneity. Today, the de facto standard for evaluating medical devices is the randomized controlled trial. However, even after years of device development many clinical trials fail. For example, in the Rhythm ID Goes Head to Head Trial (RIGHT) the risk for inappropriate therapy by implantable cardioverter defibrillators (ICDs) actually increased relative to control treatments. With recent advances in physiological modeling and devices incorporating more complex software components, population-level device outcomes can be obtained with scalable simulations. Consequently, there is a need for data-driven approaches to provide early insight prior to the trial, lowering the cost of trials using patient and device models, and quantifying the robustness of the outcome. This work presents a clinical trial modeling and statistical framework which utilizes simulation to improve the evaluation of medical device software, such as the algorithms in ICDs. First, a method for generating virtual cohorts using a physiological simulator is introduced. Next, we present our framework which combines virtual cohorts with real data to evaluate the efficacy and allows quantifying the uncertainty due to the use of simulation. Results predicting the outcome of RIGHT and improving statistical power while reducing the sample size are shown. Finally, we improve device performance with an approach using Bayesian optimization. Device performance can degrade when deployed to a general population despite success in clinical trials. Our approach improves the performance of the device with outcomes aligned with the MADIT-RIT clinical trial. This work provides a rigorous approach towards improving the development and evaluation of medical treatments.
  • Publication
    Imu-Based State Estimation And Control Of Quadrotors Exploiting Aerodynamic Effects
    (2019-01-01) Svacha, James Baird
    Quadrotors and multirotors in general are common in many inspection and surveillance applications. For these applications, visual-inertial odometry is a common way to localize the vehicles and observe the environment. However, unlike with wheeled mobile robots, quadrotor localization algorithms often do not use knowledge of the control inputs and the full vehicle dynamics as a process model for localization. Rather, they use kinematic models, with the IMU providing acceleration and angular velocity. One of the reasons for avoiding the use of dynamics is that, until recently quadrotor aerodynamic effects have not been considered in the literature and hence the dynamic models for quadrotors have been less accurate than those for wheeled mobile robots. The main aerodynamic terms that are significant are first-order effects that are linear in velocity and angular velocity. They are predominantly caused by aerodynamic interaction with the spinning propellers. This work investigates the models for such effects, as well as what can be gained if such aerodynamic effects are incorporated into the dynamic model and the full dynamics are used for state estimation. We develop novel IMU-based filters, the end results of which are used to estimate the wind velocity of the quadrotor or, indoors, when the ambient wind is zero, the velocity of the quadrotor. In addition, these filters estimate the many aerodynamic parameters in the model online. They may also be used to estimate sensor biases and inertial parameters. We demonstrate the effectiveness of these filters through experiments. We also present nonlinear observability analyses that theoretically determine the observability properties of the systems.
  • Publication
    Efficient Learning and Inference for High-dimensional Lagrangian Systems
    (2011-04-18) Vernaza, Paul N
    Learning the nature of a physical system is a problem that presents many challenges and opportunities owing to the unique structure associated with such systems. Many physical systems of practical interest in engineering are high-dimensional, which prohibits the application of standard learning methods to such problems. This first part of this work proposes therefore to solve learning problems associated with physical systems by identifying their low-dimensional Lagrangian structure. Algorithms are given to learn this structure in the case that it is obscured by a change of coordinates. The associated inference problem corresponds to solving a high-dimensional minimum-cost path problem, which can be solved by exploiting the symmetry of the problem. These techniques are demonstrated via an application to learning from high-dimensional human motion capture data. The second part of this work is concerned with the application of these methods to high-dimensional motion planning. Algorithms are given to learn and exploit the struc- ture of holonomic motion planning problems effectively via spectral analysis and iterative dynamic programming, admitting solutions to problems of unprecedented dimension com- pared to known methods for optimal motion planning. The quality of solutions found is also demonstrated to be much superior in practice to those obtained via sampling-based planning and smoothing, in both simulated problems and experiments with a robot arm. This work therefore provides strong validation of the idea that learning low-dimensional structure is the key to future advances in this field.
  • Publication
    Analysis of a Simplified Hopping Robot
    (1988-05-01) Koditschek, Daniel E; Buehler, Martin
    We offer some preliminary analytical results concerning simplified models of Raibert’s hopper. We represent the task of achieving a recurring hopping height for an actuated “ball” robot as a stability problem in the setting of a nonlinear discrete dynamical system. We model the properties of Raibert’s control scheme in a simplified fashion, and provide conditions under which the procedure results in closed loop dynamics possessed of a globally attracting fixed point - the formal rendering of what we intuitively mean by a “correct” strategy. The motivation for this work is the hope that it will facilitate the development of general design principles for “dynamically dexterous” robots. For more information: Kod*Lab
  • Publication
    Transit Technology Today
    (1984-11-01) Vuchic, Vukan R
    This keynote address was presented at the Symposium on Recent Developments in Urban Transit Technology in Taipei, Taiwan on November 27, 1984.
  • Publication
    Holistically Evaluating Agent Based Social System Models
    (2012-01-01) Bharathy, Gnana K.; Silverman, Barry G.
    The philosophical perspectives on model evaluation can be broadly classified into reductionist/logical positivist and relativist/holistic. In this paper, we outline some of our past efforts in, and challenges faced during, evaluating models of social systems with cognitively detailed agents. Owing to richness in the model, we argue that the holistic approach and consequent continuous improvement are essential to evaluating complex social system models such as these. A social system built primarily of cognitively detailed agents can provide multiple levels of correspondence, both at observable and abstract aggregated levels. Such a system can also pose several challenges, including large feature spaces, issues in information elicitation with database, experts and news feeds, counterfactuals, fragmented theoretical base, and limited funding for validation. We subscribe to the view that no model can faithfully represent reality, but detailed, descriptive models are useful in learning about the system and bringing about a qualitative jump in understanding of the system it attempts to model – provided they are properly validated. Our own approach to model evaluation is to consider the entire life cycle and assess the validity under two broad dimensions of (1) internally focused validity/quality achieved through structural, methodological, and ontological evaluations; and (2) external validity consisting of micro validity, macro validity, and qualitative, causal and narrative validity. In this paper, we also elaborate on selected validation techniques that we have employed in the past. We recommend a triangulation of multiple validation techniques, including methodological soundness, qualitative validation techniques, such as face validation by experts and narrative validation, and formal validation tests, including correspondence testing.
  • Publication
    Transportation for Liveable Cities: Problems, Obstacles, and Successful Solutions
    (2010-01-01) Vuchic, Vukan R
    This chapter focuses on urban transportation. It is written by the moderator of the session on Land Transportation. He asked the five speakers to report on positive achievements and challenges in their cities or countries. The chapter starts with the moderator's review of developments and trends in urban transportation and a summary of the five reports by participants presented in the session. It is followed by a brief review of the conditions in urban transportation and its impact on cities. Following a review of problems most cities face and mistakes in transportation planning many cities continue to make, this chapter places emphasis on progressive policies and successful solutions which feasibility has been demonstrated by a number of leading cities.
  • Publication
    Autonomous Behaviors With A Legged Robot
    (2018-01-01) Ilhan, Berkay Deniz
    Over the last ten years, technological advancements in sensory, motor, and computational capabilities have made it a real possibility for a legged robotic platform to traverse a diverse set of terrains and execute a variety of tasks on its own, with little to no outside intervention. However, there are still several technical challenges to be addressed in order to reach complete autonomy, where such a platform operates as an independent entity that communicates and cooperates with other intelligent systems, including humans. A central limitation for reaching this ultimate goal is modeling the world in which the robot is operating, the tasks it needs to execute, the sensors it is equipped with, and its level of mobility, all in a unified setting. This thesis presents a simple approach resulting in control strategies that are backed by a suite of formal correctness guarantees. We showcase the virtues of this approach via implementation of two behaviors on a legged mobile platform, autonomous natural terrain ascent and indoor multi-flight stairwell ascent, where we report on an extensive set of experiments demonstrating their empirical success. Lastly, we explore how to deal with violations to these models, specifically the robot's environment, where we present two possible extensions with potential performance improvements under such conditions.
  • Publication
    Propagation of Schedule Disturbances in Line-Haul Passenger Transportation
    (1969) Vuchic, Vukan R
    Schedule disturbances in public transport operations have a tendency to intensify along the line and propagate to successive vehicles due to the uneven accumulation of passengers. This phenomenon, affecting efficiency and reliability of service, occurs frequently with surface services due to street congestion, as well as with rapid transit when It approaches capacity volumes. In recent years, considerable attention has been given to this problem. Newell and Potts [1] (*), using a deterministic model, derived an expression for the behavior of delays both along the line and of subsequent vehicles at individual stations due to passenger accumulation. They gave a theoretical explanation of the phenomenon of pairing of buses, which later Potts and Tamlin tried to verify through observations of bus operations [2]. While they did observe the tendency for pairing of vehicles, their experiment indicated that numerous other factors in street operation (signals, traffic, etc.) make it difficult to distinguish individual causes of delays. Rapid transit is more convenient for these observations since passenger boarding is the dominant variable factor in operation. Tiercin [3] described a new method of schedule control tested by RATP in Paris for one of the principal « Metro » lines, and London Transport, in planning for « Victoria Line», used computer simulation of rapid transit operation at minimum intervals to derive operational measures to increase stability of service. This work was reported by Welding and Day (4) and in an unpublished Research Report [5]. Recently, Lehmann [6] and Sudmeyer [7] gave an Interesting theoretical analysis of propagation of delays along the line; their discussion was followed by a paper by this author [8] which is incorporated and somewhat expanded here. In this paper a theoretical analysis of the behavior of disturbances is extended to include the changes of disturbances with time (for subsequent vehicles at any given station). Practical implications are discussed and measures to minimize this phenomenon in public transport operations are suggested. A diagram for easy evaluation of stability of any service is also given here.