TY - GEN
T1 - Parallelization of path planning algorithms for AUVs concepts, opportunities, and program-technical implementation
AU - Eichhorn, Mike
AU - Woithe, Hans Christian
AU - Kremer, Ulrich
PY - 2012
Y1 - 2012
N2 - Modern autonomous underwater vehicles (AUVs) have advanced sensing capabilities including sonar, cameras, acoustic communication, and diverse bio-sensors. Instead of just sensing its environment and storing the data for post-mission inspection, an AUV could use the collected information to gain an understanding of its environment, and based on this understanding autonomously adapt its behavior to enhance the overall effectiveness of its mission. Many such tasks are highly computation intensive. This paper presents the results of a case study that illustrates the effectiveness of an energy-aware, many-core computing architecture to perform on-board path planning within a battery-operated AUV. A previously published path planning algorithm was ported onto the SCC, an experimental 48 core single-chip system developed by Intel. The performance, power, and energy consumption of the application were measured for different numbers of cores and other system parameters. This case study shows that computation intensive tasks can be executed within an AUV that relies mainly on battery power. Future plans include the deployment and testing of an SCC system within a Teledyne Webb Research Slocum glider.
AB - Modern autonomous underwater vehicles (AUVs) have advanced sensing capabilities including sonar, cameras, acoustic communication, and diverse bio-sensors. Instead of just sensing its environment and storing the data for post-mission inspection, an AUV could use the collected information to gain an understanding of its environment, and based on this understanding autonomously adapt its behavior to enhance the overall effectiveness of its mission. Many such tasks are highly computation intensive. This paper presents the results of a case study that illustrates the effectiveness of an energy-aware, many-core computing architecture to perform on-board path planning within a battery-operated AUV. A previously published path planning algorithm was ported onto the SCC, an experimental 48 core single-chip system developed by Intel. The performance, power, and energy consumption of the application were measured for different numbers of cores and other system parameters. This case study shows that computation intensive tasks can be executed within an AUV that relies mainly on battery power. Future plans include the deployment and testing of an SCC system within a Teledyne Webb Research Slocum glider.
KW - AUV Slocum Glider
KW - Graph methods
KW - Path Planning
KW - Single-chip Cloud Computer
KW - parallel programming
KW - time varying environment
UR - https://www.scopus.com/pages/publications/84866710401
UR - https://www.scopus.com/pages/publications/84866710401#tab=citedBy
U2 - 10.1109/OCEANS-Yeosu.2012.6263557
DO - 10.1109/OCEANS-Yeosu.2012.6263557
M3 - Conference contribution
AN - SCOPUS:84866710401
SN - 9781457720895
T3 - Program Book - OCEANS 2012 MTS/IEEE Yeosu: The Living Ocean and Coast - Diversity of Resources and Sustainable Activities
BT - Program Book - OCEANS 2012 MTS/IEEE Yeosu
T2 - OCEANS 2012 MTS/IEEE Yeosu Conference: The Living Ocean and Coast - Diversity of Resources and Sustainable Activities
Y2 - 21 May 2012 through 24 May 2012
ER -