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    Results and Conclusions: Perception Sensor Study for High Speed

    Autonomous Operations Anne Schneidera, Zachary LaCellea, Alberto Lacazea, Karl Murphya, Ryan Closeb

    aRobotic Research, LLC, Gaithersburg, MD; bUS Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate,

    Fort Belvoir, VA

    ABSTRACT

    Previous research has presented work on sensor requirements, specifications, and testing, to evaluate the

    feasibility of increasing autonomous vehicle system speeds. Discussions included the theoretical background for

    determining sensor requirements, and the basic test setup and evaluation criteria for comparing existing and

    prototype sensor designs. This paper will present and discuss the continuation of this work. In particular, this

    paper will focus on analyzing the problem via a real-world comparison of various sensor technology testing

    results, as opposed to previous work that utilized more of a theoretical approach. LADAR/LIDAR, radar, visual,

    and infrared sensors are considered in this research. Results are evaluated against the theoretical, desired

    perception specifications. Conclusions for utilizing a suite of perception sensors, to achieve the goal of doubling

    ground vehicle speeds, is also discussed.

    Keywords: Sensors, high-speed, autonomy, LADAR, LIDAR

    1. INTRODUCTION

    One of the most difficult challenges in the field of autonomous ground robotics is increasing the maximum

    operational speed of vehicles. In order to safely increase speed, the vehicle must be able to perceive and make

    decisions based upon the surrounding environment. Currently, state-of-the-art robotic systems utilize LADARs

    (LAser Detection And Ranging), also referred to as LIDARs (LIght Detection And Ranging) as the primary

    perception sensor. LADARs measure the distance to a point by emitting a laser beam and analyzing the reflected

    light. Time-of-flight LADAR systems convert the roundtrip time of the laser (i.e., the time it takes the laser to

    reach an object and reflect back to the sensor) into a distance measurement.

    In [1], we presented the initial results from a sensor study aimed to analyze, both from a theoretical perspective

    and using real-world data, what sensor specifications are required for high speed (i.e., 60mph) driving. This

    initial portion of the study mostly focused on a theoretical analysis. While the derivation of these specifications

    will not be repeated in this paper, a summary of the findings for a HMMWV vehicle can be seen in Table 1.

    Table 1: Desired Specifications for 60mph driving with a HMMWV

    Range Vertical Field of

    View

    Horizontal Field

    of View

    Vertical Angular

    Resolution

    (Positive

    Obstacle)

    Vertical Angular

    Resolution

    (Negative

    Obstacle)

    123m 123 140 0.1 0.0032

    The remainder of [1] discusses the test setup for the real-world sensor testing, along with some initial results from

    a first round of testing involving three commonly used sensors for robotic platforms. This paper will further

    expand upon the results from the real-world sensor testing, including results from a total of seven different

    evaluated LADARs.

  • 2. SENSOR STUDY RESULTS

    2.1. Evaluated LADAR Sensors

    A variety of different LADAR sensors were tested in this study. The Velodyne HDL-64E S2, the GDRS

    microLADAR, and the IBEO LUX 8L were chosen because each one has been utilized in major robotics projects

    (e.g., the DARPA Urban Challenge, USASOCs Small Unit Support IED-defeat (SUSI) program, TARDECs

    Autonomous Mobility Applique System (AMAS)). Three other tested LADARs were manufactured by Optech,

    and each are marketed towards different applications (the ILRIS-HD for surveying, the Lynx SG1 for mapping,

    and the LRM is a prototype sensor for the Canadian Space Agency). The final tested sensor was the Neptec

    OPAL-ECR, which is a newly developed sensor (available late 2015), designed for long range (>200m), real-time

    scanning in harsh environments (such as mining and construction), and has obscurant penetration capabilities.

    Some of the specifications for these LADAR sensors can be seen in Table 2.

    Table 2. LADAR specifications

    LADAR Velodyne

    HDL-64E S2

    GDRS XR

    microLADAR IBEO

    LUX 8L

    Optech

    ILRIS-HD

    Optech

    Lynx SG1

    Optech

    LRM

    Neptec

    OPAL-

    ECR

    Wavelength 905nm 905nm 905nm 1535nm

    15XXnm 1500nm 1550nm

    Range 120m at ~80%

    reflectivity

    50m at ~10%

    reflectivity

    120m 200m for

    average

    target5

    50m at

    ~10%

    reflectivity

    1250m 250m @

    10%

    reflectivity

    120m 240m 80%

    reflectivity

    240m

    10%

    reflectivity

    Number of

    Lasers

    64 1 8 1 2 (1 per

    sensor)

    1 1

    Scan

    Frequency

    5-15 Hz 10 Hz 25 Hz Unknown Up to 500

    lines per

    second

    5 Hz 25Hz

    (Typical)

    Field of

    View

    HFOV: 360

    VFOV: 26.8

    (= 2,

    = 24.8)

    HFOV: 120

    VFOV: 20

    (= 10,

    = 10)

    HFOV:

    110

    VFOV:

    6.4

    (= -

    3.2,

    =

    3.2)

    H: 40

    V: 40

    (adjustable)

    360 HFOV:

    60

    VFOV:

    50

    120o

    Conical

    (=

    60,

    =

    60)

    Vertical

    Angular

    Resolution

    0.4 Variable

    (non-

    overlapping

    scan pattern)

    0.8 0.001146 N/A Unknown Variable

    within the

    FOV

    0.036o

    within +/-

    10o from

    the FOV

    center line

    Horizontal

    Angular

    Resolution

    0.09 Variable

    (non-

    overlapping

    scan pattern)

    Up to

    0.125

    0.001146 Unknown Unknown Variable

    within the

    FOV

    0.036o

    within +/-

    10o from

  • The Velodyne 64 returns many more points per second than the other LADARs being evaluated, in part because it

    has multiple (64) scan lines. The 64 lasers are rotated to obtain a 360 horizontal field of view. The IBEO LUX

    8L is also a multi-line scanner (it contains two groups of four lasers, each), but has a smaller vertical and

    horizontal field of view than the Velodyne. The XR microLADAR and Neptec OPAL-ECR are unique, because

    they feature non-overlapping scan patterns. A single laser is internally moved to allow for two degrees of

    freedom azimuth and elevation angle. This creates a non-overlapping scan pattern, which means that a very

    dense point cloud can be created when the vehicle is not in motion. However, this can be a disadvantage at higher

    speeds, as the sensors only have a single laser to cover the field of view, as compared to the multi-line scanners;

    hence, they do not return as many points per second, leading to less dense point clouds.

    The Neptec and Optech sensors operate in the SWIR wavelength, and are therefore capable of much longer ranges

    than the more commonly used 905nm sensors. This is because the power can be increased on the SWIR lasers,

    while still remaining eye-safe. The ILRIS scanner has the longest range (>1000m) of all the sensors being tested.

    Additionally, the beam divergence is much smaller. However, because the sensor is designed for detailed

    surveying applications, the scan times are relatively slow, which makes it less applicable for high speed platforms.

    As we will discuss further in following sections, we were able to speed up the scans to some extent by reducing

    the FOV and number of points returned per scan. The Lynx is a two-sensor system that is mounted on the back of

    a vehicle. Each sensor has a single scan line, and is mounted at an angle, scanning to the side of the vehicle.

    Because this is not a forward scanning LADAR, we adjusted some of the tests to be more appropriate for the scan

    pattern. Lastly, the LRM is a prototype, 2-axis scanner developed for the Canadian Space Agency. This is the

    only 2-axis scanner from Optech that was evaluated.

    2.2. Static Obstacle Results

    In [1], we presented the static obstacle test setup, along with some preliminary results (Figure 1) for three of the

    LADAR sensors that were evaluated in this study. The following section will elaborate on those results, in

    addition to discussing the additional sensors that were tested in the later part of this study.

    the FOV

    center line

    Beam

    Divergence

    2.0 mrad 3.2 mrad Unknown 150 rad Unknown 0.35

    mrad

    0.6 mrad

  • 2.2.1. Velodyne 64, GDRS microLADAR, and IBEO LUX 8L Results

    Figure 1. LADAR point clouds from three different sensors. The data was captured at 30mph and is plotted from

    200m from the first objects until the vehicle has reached the objects. (top) Image of test setup with different objects

    highlighted in various colors. Each of the point cloud images, below, is labeled with the same colors. (bottom left)

    Velodyne HDL-64E point cloud. (bottom middle) GDRS XR microLADAR point cloud. (bottom right) IBEO LUX

    8L point cloud.

    Figure 1 shows all of the points collected on the objects, starting from when the vehicle was 200m away from the

    obstacles, until the vehicle was in-line with the first row of obstacles. However, this view of the data is not the

    most useful t