The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In the Multi-Policy Decision Making (MPDM) framework, a robot's policy is elected by sampling from the distribution of current states, predicting future outcomes through forward simulation, and selecting the policy with the best expected performance. Electing the best plan depends on sampling initial conditions with influential (very high costs) outcomes. Discovering these configurations through random...
In GPS-denied environments, robot systems typically revert to navigating with dead-reckoning and relative mapping, accumulating error in their global pose estimate. In this paper, we propose Feature-based Localization between Air and Ground (FLAG), a method for computing global position updates by matching features observed from ground to features in an aerial image. Our method uses stable, descriptorless...
This paper reports on an integrated inference and decision-making approach for autonomous driving that models vehicle behavior for both our vehicle and nearby vehicles as a discrete set of closed-loop policies. Each policy captures a distinct high-level behavior and intention, such as driving along a lane or turning at an intersection. We first employ Bayesian changepoint detection on the observed...
The goal of this paper is to develop a robot with a grounded spatial vocabulary. Such a vocabulary would allow it to give and follow directions, and would give it valuable additional information in aiding localization and navigation. We approach the problem by defining an ontology of space (including corridor, doorway, and room) and by creating a Convolutional Neural Network (CNN) that allows the...
AprilTags and other passive fiducial markers require specialized algorithms to detect markers among other features in a natural scene. The vision processing steps generally dominate the computation time of a tag detection pipeline, so even small improvements in marker detection can translate to a faster tag detection system. We incorporated lessons learned from implementing and supporting the AprilTag...
Matching 3D point clouds, a critical operation in map building and localization, is difficult with Velodyne-type sensors due to the sparse and non-uniform point clouds that they produce. Standard methods from dense 3D point clouds are generally not effective. In this paper, we describe a feature-based approach using Principal Components Analysis (PCA) of neighborhoods of points, which results in mathematically...
Many autonomous vehicles require precise localization into a prior map in order to support planning and to leverage semantic information within those maps (e.g. that the right lane is a turn-only lane.) A popular approach in automotive systems is to use infrared intensity maps of the ground surface to localize, making them susceptible to failures when the surface is obscured by snow or when the road...
In dynamic environments crowded with people, robot motion planning becomes difficult due to the complex and tightly-coupled interactions between agents. Trajectory planning methods, supported by models of typical human behavior and personal space, often produce reasonable behavior. However, they do not account for the future closed-loop interactions of other agents with the trajectory being constructed...
Mobile robotic teams require robust communication in order to coordinate effectively, which is a challenge given the dynamic, unpredictable nature of mobile ad hoc networks (MANET). These networks are subject to rapidly varying link qualities as robots move through their environment. Improving the robustness of these point-to-point links leads to greater overall network performance, which in turn...
This paper describes the architecture and implementation of an autonomous passenger vehicle designed to navigate using locally perceived information in preference to potentially inaccurate or incomplete map data. The vehicle architecture was designed to handle the original DARPA Urban Challenge requirements of perceiving and navigating a road network with segments defined by sparse waypoints. The...
Mid-way through the 2007 DARPA Urban Challenge, MIT’s robot ‘Talos’ and Team Cornell’s robot ‘Skynet’ collided in a low-speed accident. This accident was one of the first collisions between full-sized autonomous road vehicles. Fortunately, both vehicles went on to finish the race and the collision was thoroughly documented in the vehicle logs. This collaborative study between MIT and Cornell traces...
Orientation estimates derived from gyroscopes are limited in quality by the noise and bias characteristics of the sensors. Presently, there is a large gap in price and performance between high-end fiber-optic gyroscopes and inexpensive MEMS gyroscopes. In this paper, we propose using a redundant array of inexpensive gyroscopes (RAIG) in order to obtain significant improvements in performance. A naïve...
This paper reports on an algorithm to support autonomous vehicles in reasoning about occluded regions of their environment to make safe, reliable decisions. In autonomous driving scenarios, other traffic participants are often occluded from sensor measurements by buildings or large vehicles like buses or trucks, which makes tracking dynamic objects challenging.We present a method to augment standard...
Image feature descriptors composed of a series of binary intensity comparisons yield substantial memory and runtime improvements over conventional descriptors, but are sensitive to viewpoint changes in ways that vary per feature. We propose a method to improve the matching performance of such descriptors by specifically reasoning about the reliability of test results on a feature-by-feature basis...
We consider the problem of a human-following robot in which a human is equipped with a low-fidelity odometry sensor and a robot follows the human leader — often lagging well behind and out of visual contact with the human. The challenge is for the robot to determine the path taken by the human, despite the relatively noisy odometry data available. Such a system is useful in a “pack mule” application,...
This paper proposes an integrated motion planning and control approach for autonomous car navigation. Existing approaches to autonomous vehicle navigation typically plan a trajectory and pass it on to a steering controller that commands steering wheel angle (SWA) or curvature at every timestep to minimize tracking error. However, this approach exhibits large amounts of control effort, and ignores...
We describe a new multi-resolution scan matching method that makes exhaustive (and thus local-minimum-proof) matching practical, even for large positional uncertainties. Unlike earlier multi-resolution methods, in which putative matches at low-resolutions can lead the matcher to an incorrect solution, our method generates exactly the same answer as a brute-force full-resolution method. We provide...
Real-world autonomous driving in city traffic must cope with dynamic environments including other agents with uncertain intentions. This poses a challenging decision-making problem, e.g., deciding when to perform a passing maneuver or how to safely merge into traffic. Previous work in the literature has typically approached the problem using ad-hoc solutions that do not consider the possible future...
A homography is traditionally formulated as a linear transformation and is used in multiple-view geometry as a linear map between projective planes (or images). Analogous to the use of homography-based techniques to calibrate a pin-hole camera, non-linear homographies extend the pin-hole camera model to deal with non-linearities such as lens distortion
Visual odometry is typically formulated as a descriptor-based image feature tracking problem, followed by outlier rejection and simultaneous estimation of the scene structure and camera motion. We propose a fundamentally different formulation for the stereo case: a multi-scale search over pose to estimate the transformation that best aligns two sparse point clouds in image space. This has three main...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.