Performance Assessment of Prediction In Dynamic Environments (PRIDE) in Manufacturing Environments

Conference · Thu Jan 01 04:00:00 EST 2009

OSTI ID:965324

Kootbally, Zeid ^[1]; Schlenoff, Craig ^[1]; Madhavan, Raj ^[2]

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1. National Institute of Standards and Technology (NIST)
2. ORNL

This paper describes PRIDE (Prediction in Dynamic Environments), a multi-resolution and hierarchical framework. PRIDE was developed as a test bed to assess the performance of autonomous vehicles in the presence of moving objects in a simulated environment. By simulating scenarios in which moving objects are prevalent, a designer of an autonomous vehicle can test the performance of their path planning and collision avoidance algorithms without having to immerse the vehicle in the physical world. This framework supports the prediction of the future location of moving objects at various levels of resolution, thus providing prediction information at the frequency and level of abstraction necessary for planners at different levels within the hierarchy. Previous works have demonstrated the reliability of PRIDE to simulate on-road traffic situations with multiple vehicles. To provide realistic scenarios, PRIDE integrates a level of situation awareness of how other vehicles in the environment are expected to behave considering the situation in which the vehicles find themselves in. In recent efforts, the PRIDE framework has been extended to consider production logistics in dynamic manufacturing environment while focusing on the scheduling of material transportation system. To demonstrate the characteristics of the PRIDE framework, this paper illustrates real-time navigation of Automated Guided Vehicles (AGVs) at different locations in a dynamic manufacturing environment. Moreover, using the high-fidelity physics?based framework for the Unified System for Automation and Robot Simulation (USARSim), this paper analyzes the performance of the PRIDE framework on a set of realistic scenarios.

• Research Organization: Oak Ridge National Laboratory (ORNL)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 965324
• Country of Publication: United States
• Language: English

Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
ALGORITHMS
AUTOMATION
AVOIDANCE
FOCUSING
FORECASTING
MANUFACTURING
NAVIGATION
PERFORMANCE
PLANNING
PRODUCTION
RELIABILITY
RESOLUTION
ROBOTS
TRANSPORTATION SYSTEMS