Herein is described a method which objective is to enhance the speed at which terrain inter visibility calculations are performed for unknown or "pop-up" ground based radar threats. The problem with current inter visibility techniques is their inability to perform in real time, thereby jeopardizing the survivability and success of the mission. The main computational hurdle is the intensive checking of the radar extensions against the surrounding terrain. These very repetitive line-of-sight calculations result in a detailed mapping of volumes within which an object is non-detectable. We outline a set of high level methods which checks a selected set of lines for intersect with a subset of terrain elements.
A rapid sorting technique with a wide range of applications has been developed and performance tested. The applications include path planning for complex manipulators with many degrees of freedom and autonomous under water vehicles. This paper describes the results and trade-offs behind the design and implementation phases during hardware and software development. The presented sorting technique is particularly useful as a collision checking, or conversely homing, subroutine in path planning in complex and dynamic environments.
A new set of collision checking and obstacle avoidance algorithms has been developed and implemented in both hardware and software. The method allows for unlimited vector checks against an unlimited set of objects. Dependent upon the application, the single card hardware performance ranges from 1 million line sorts per second to hundreds of millions. Therefore, due to the high algorithm speed, the overall system performance only becomes limited by the choice of processor and the speed of the interface. The hardware is presently configured to process large blocks of objects and data (8K) at a sorting rate of one point against eight objects at a rate of 200 million points per second. The trade-off between choice of algorithm and performance is discussed.
As is well know, collision checking in a generalized sense is a substantial contributor to processor load in a wide range of path-planning applications. These include high-speed terrain following and obstacle avoidance in low-flying aircraft, path planning on local scales for autonomous vehicles, both undersea and on land, and a number of areas in robotic motion planning, not only for mobile robot navigation but also for such problems as arm motion in cluttered environments. Some algorithms have been quoted as requiring from 80% to as much as 95% of the available path-planning time for collision checking. Under such conditions, special-purpose hardware designed for the requirements of collision checking offers the promise of major overall performance improvements in real-time path planning. Recent work at the Lockheed Palo Alto Research Laboratories has produced a hardware system providing a major acceleration in collision-checking capability with minimal added hardware, and demonstrated an approach leading to still further major increments in speed for this function. This paper first describes the architecture of the system, which is known as TIGER (Three- dimensional Intersect & Geometrical Evaluator in Real time). This is followed by an analysis of the computational load of the collision-checking problem and a discussion of important design and performance considerations arising from the approach both within TIGER itself and in the integration of TIGER into a higher-level path-planning system.
KEYWORDS: Sensors, Data conversion, Data modeling, 3D modeling, Environmental sensing, Optical resolution, Data analysis, Data processing, Sensor performance, 3D acquisition
In order to perform real-time signal processing and data analysis of fused sensor data and at the same time optimize the use of existing hardware, the scene information most often has to be converted into a particular format. In general, this format conversion is viewed as part of the sensor fusion process, but in this paper it will be treated as a separate entity. In other words, the concentration is on building a representation of the environment which lends itself directly to real-time true three-dimensional processing of the environment with higher-level path planning in mind. An example scenario is using the data as input for terrain-following and terrain-avoidance algorithms, where the output from the sensor data processing is a world model that directly applies to intersect analysis and evaluation. The intersect processing is performed in a hardware unit called the TIGER (three-dimensional intersect & geometrical evaluator in real time). The TIGER is based on VHSIC (very-high-speed integrated-circuit) technology, and performs intersect calculations at rates of the order of millions of objects/sec using a particular three-dimensional object format. This hardware subsystem is designed to be useful for a wide range of airborne, underwater and space applications. In order to address a broad area of sensor types, the architecture is made generic, and has potential applications in solving selected sensor-fusion computational bottlenecks as well. Standard interfaces simplify subsystem coupling to a variety of host processor systems. The TIGER hardware has been built and tested extensively.
KEYWORDS: Sensors, Signal processing, Image processing, Environmental sensing, 3D acquisition, Data processing, Spherical lenses, Data integration, Clocks, Binary data
Efficient high-speed algorithms are in great demand for applications in which the geometrical configuration of the environment must be assessed before a subsequent move can be performed. The knowledge of the spatial configuration of the object distribution is either a priori or obtained from fused and converted sensor data. The new method can: (1) readily implement known and new sensor data inputs (2) process the resulting geometry in three-dimensional space for location and intersect and (3) permit a system response with a best path in less than a second. Due to its simple architecture the system can treat threats targets terrain and moving objects in the same hardware. 1.
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