Proc. SPIE. 10195, Unmanned Systems Technology XIX
KEYWORDS: Long wavelength infrared, Warfare, Data modeling, Cameras, LIDAR, Sensors, Calibration, Robotics, Computing systems, 3D modeling, Computer vision technology, Navigation systems, Systems engineering, Environmental sensing, Systems modeling, Unmanned systems, Global Positioning System
In 2010 the ONR Code 30 Irregular and Expeditionary Warfare Department began a long-term strategic investment in ground system autonomy focused on supporting our Expeditionary forces, namely the United States Marine Corps (USMC). The Marine Corps' mission and challenges are unique and as such require unique capabilities of the autonomous systems they will employ. For the past six years ONR Code 30 has been executing the Multi-role Autonomous Ground Vehicle (MAGV) program which has focused on developing core technologies to enable the operation of autonomous ground vehicles in expeditionary environments. The key overarching tenets of the program have been to develop a ground autonomy system that is affordable, can operate in those expeditionary (off-route) environments, and which will be the technological foundation for future DoD programs both in S and T and acquisition. Those three key tenets have driven many of the investment decisions of the program including a focus on low-cost sensors and computation (e.g., vision systems), congested environment motion planning, operation under degraded GPS conditions, multi-vehicle coordination, and using a rapid development and evolutionary systems engineering approach with rigorous and consistent performance evaluations. This paper describes the goals and objectives of the ONR 30 ground autonomy program and provides an overview of the technical accomplishments that have been achieved over the past six years.
The Velodyne HDL-64E is a 64 laser 3D (360×26.8 degree) scanning LIDAR. It was designed to fill perception
needs of DARPA Urban Challenge vehicles. As such, it was principally intended for ground use. This paper
presents the performance of the HDL-64E as it relates to the marine environment for unmanned surface vehicle
(USV) obstacle detection and avoidance. We describe the sensor's capacity for discerning relevant objects at sea-
both through subjective observations of the raw data and through a rudimentary automated obstacle detection
algorithm. We also discuss some of the complications that have arisen with the sensor.
This paper presents a pose estimation method based on a 3D camera - the SwissRanger SR4000. The proposed method
estimates the camera's ego-motion by using intensity and range data produced by the camera. It detects the SIFT (Scale-
Invariant Feature Transform) features in one intensity image and match them to that in the next intensity image. The
resulting 3D data point pairs are used to compute the least-square rotation and translation matrices, from which the
attitude and position changes between the two image frames are determined. The method uses feature descriptors to
perform feature matching. It works well with large image motion between two frames without the need of spatial
correlation search. Due to the SR4000's consistent accuracy in depth measurement, the proposed method may achieve a
better pose estimation accuracy than a stereovision-based approach. Another advantage of the proposed method is that
the range data of the SR4000 is complete and therefore can be used for obstacle avoidance/negotiation. This makes it
possible to navigate a mobile robot by using a single perception sensor. In this paper, we will validate the idea of the
pose estimation method and characterize the method's pose estimation performance.
Space and Naval Warfare Systems Center, San Diego (SSC San Diego) has developed an unmanned vehicle and sensor operator control interface capable of simultaneously controlling and monitoring multiple sets of heterogeneous systems. The modularity, scalability and flexible user interface of the Multi-robot Operator Control Unit (MOCU) accommodates a wide range of vehicles and sensors in varying mission scenarios. MOCU currently controls all of the SSC San Diego developmental vehicles (land, air, sea, and undersea), including the SPARTAN Advanced Concept Technology Demonstration (ACTD) Unmanned Surface Vehicle (USV), the iRobot PackBot, and the Family of Integrated Rapid Response Equipment (FIRRE) vehicles and sensors. This paper will discuss how software and hardware modularity has allowed SSC San Diego to create a single operator control unit (OCU) with the capability to control a wide variety of unmanned systems.
The US Navy and other Department of Defense (DoD) and Department of Homeland Security (DHS) organizations are increasingly interested in the use of unmanned surface vehicles (USVs) for a variety of missions and applications. In order for USVs to fill these roles, they must be capable of a relatively high degree of autonomous navigation. Space and Naval Warfare Systems Center, San Diego is developing core technologies required for robust USV operation in a real-world environment, primarily focusing on autonomous navigation, obstacle avoidance, and path planning.
Many advances have been made in autonomy for unmanned ground vehicles (UGVs) but most of these advances have been for large UGVs only, in that the sensors required for autonomy are typically large, heavy and require a significant amount of power. Because of the size, weight and power restrictions imposed by a man-portable UGV advances in autonomy have been very limited. The SPAWAR Systems Center San Diego (SSC San Diego) has previously developed a waypoint navigation capability for small robots. That system required an operator to monitor a live video feed from the vehicle to ensure it did not strike any obstacles in its path. Now SSC San Diego in cooperation with the NASA Jet Propulsion Laboratory (JPL) has developed a miniature obstacle detection sensor suitable for small robots. SSC San Diego has also developed the obstacle-avoidance algorithms to navigate autonomously around obstacles.
Development of Unmanned Ground Vehicles (UGVs) has been ongoing for decades. Much of the technology developed for UGVs can be applied directly to Unmanned Surface Vehicles (USVs) with little or no modification. SPAWAR Systems Center San Diego (SSC San Diego) has successfully demonstrated this by transitioning technology (both hardware and software) from a man-portable UGV to a USV demonstrator platform. By transitioning technology already proven in a UGV, SSC San Diego was able to develop a working USV much more quickly than would have been otherwise possible. The technologies ported from the UGV to the USV include: the software architecture and protocol, teleoperation, a Kalman filter for state estimates, waypoint navigation, the Operator Control Unit (OCU), miniature processors, Ethernet switches and a video CODEC board.
The Man Portable Robotic System (MPRS) project objective was to build and deliver hardened robotic systems to the U.S. Army's 10th Mountain Division in Fort Drum, New York. The systems, specifically designed for tunnel and sewer reconnaissance, were equipped with visual and audio sensors that allowed the Army engineers to detect trip wires and booby traps before personnel entered a potentially hostile environment. The greatest challenges for the project stemmed from the users three main requirements: 1) man-portable (lightweight and small), 2) waterproof (not just water-resistant), and 3) soldier proof(highly rugged and reliable). The MPRS systems were, of course, plagued by the usual problems in robotics: limited battery power (run-time) and limited communications range. At the Army's request, the systems incorporated no autonomous functionality; however, MPRS did integrate several state-of-the-art components, including a fully digital video system. This paper discusses specific challenges encountered and lessons learned by the MPRS team during recent tunnel and sewer reconnaissance testing at three sites in 2000: Fort Drum (New York), Fort Leonard Wood (Missouri), and Fort Polk (Louisiana).