Now showing items 11-22 of 22

    • Industrial-Scale Autonomous Wheeled-Vehicle Path Following by Combining Iterative Learning Control with Feedback Linearization 

      Dekker, Lukas G.; Marshall, Joshua A.; Larsson, Johan (2017-09-30)
      Abstract— This paper presents a path following method for autonomous wheeled vehicles that combines iterative learning control (ILC) with nonlinear feedback linearization (FBL) to provide anticipatory control action ...
    • Iterative Learning-Based Admittance Control for Autonomous Excavation 

      Fernando, Heshan; Marshall, Joshua A; Larsson, Johan (Springer Netherlands, 2019-02-07)
      This paper presents the development and field validation of an iterative learning-based admittance control algorithm for autonomous excavation in fragmented rock using robotic wheel loaders. An admittance control strategy ...
    • The LiDAR Compass: Extremely Lightweight Heading Estimation with Axis Maps 

      Gallant, Marc J.; Marshall, Joshua A. (2016-09-23)
      This paper introduces the LiDAR compass, a bounded and extremely lightweight heading estimation technique that combines a two-dimensional laser scanner and axis maps, which represent the orientations of flat surfaces in ...
    • Mining Robotics 

      Marshall, Joshua; Bonchis, Adrian; Nebot, Eduardo; Scheding, Steve (Springer, 2016)
      This chapter presents an overview of the state of the art in mining robotics, from surface to underground applications, and beyond. Mining is the practice of extracting resources for utilitarian purposes. Today, the ...
    • Mobile LiDAR-Based Convergence Detection in Underground Tunnel Environments 

      Lynch, Brian K.; Marr, Jordan; Marshall, Joshua A.; Greenspan, Michael (2017-04-06)
      This paper presents a mobile LiDAR-based method for remotely identifying convergence (i.e., naturally occurring deformation) in excavated underground tunnel environments. A mobile LiDAR system is used to collect and generate ...
    • On the Design and Selection of Vehicle Coordination Policies for Underground Mine Production Ramps 

      Pasternak, Michal; Marshall, Joshua A. (2016-02-23)
      Traffic management in underground mines, especially on production ramps, is a difficult problem to optimize and control. Most operations use one of a few common policies; e.g., the so-called “lock-out” and “loaded-vehicle ...
    • Registration of Noisy Point Clouds Using Virtual Interest Points 

      Ahmed, Mirza Tahir; Mohamad, Mustafa; Marshall, Joshua A.; Greenspan, Michael (2016-03-04)
      A new method is presented for robustly and efficiently registering two noisy point clouds. The registration is driven by establishing correspondences of virtual interest points, which do not exist in the original point ...
    • Towards Controlling Bucket Fill Factor in Robotic Excavation by Learning Admittance Control Setpoints 

      Fernando, Heshan A.; Marshall, Joshua A.; Almqvist, H°akan; Larsson, Johan (2017-09-30)
      This paper investigates the extension of an admittance control scheme to- ward learning and adaptation of its setpoints to achieve controllable bucket fill factor for robotic excavation of fragmented rock. A previously ...
    • Towards Extracting Absolute Roughness From Underground Mine Drift Profile Data 

      Watson, Curtis; Marshall, Joshua A. (2016-03-08)
      The purpose of this paper is to demonstrate a technique to utilize underground mine drift profile data for estimating absolute roughness of an underground mine drift in order to implement the Darcy-Weisbach equation for ...
    • Towards Intensity-Augmented SLAM with LiDAR and ToF Sensors 

      Hewitt, Robert A.; Marshall, Joshua A. (2016-02-24)
      Although passive sensors are widely used for many mobile robotics applications that perform mapping and localization functions, there are many environments (e.g., mining and planetary) where active sensors are more practical. ...
    • Two Dimensional Axis Mapping using LIDAR 

      Gallant, Marc J.; Marshall, Joshua A. (2016-02-04)
      Abstract—This paper introduces two-dimensional axis mapping, which estimates axis maps (AMs) based on LiDAR measurements. An AM describes the dominant orientations of surfaces in an environment, and is void of positional ...
    • Visual Indoor Positioning with a Single Camera Using PnP 

      Deretey, Edith; Ahmed, Mirza Tahir; Marshall, Joshua A.; Greenspan, Michael (2016-02-23)
      This paper introduces an accurate and inexpensive method for localizing a calibrated monocular camera in 3D indoor environments. The objective of this work is to localize in 6 degrees-of-freedom (6 DOF) in the presence of ...