TY - GEN
T1 - Maximizing the Use of Computational Resources in Multi-Camera Feedback Control
AU - Henriksson, Dan
AU - Olsson, Tomas
PY - 2004
Y1 - 2004
N2 - In vision-based feedback control systems, the time to obtain sensor information is usually non-negligible, and these systems thereby possess fundamentally different timing behavior compared to standard real-time control applications. For many image-based tracking algorithms, however, it is possible to trade-off the computational time versus the accuracy of the produced position/orientation estimates.This paper presents a method for optimizing the use of computational resources in a multi-camera based positioning system. A simplified equation for the covariance of the position estimation error is calculated, which depends on the set of cameras used and the number of edge detection points in each image. An efficient algorithm for selection of a suitable subset of the available cameras is presented, which attempts to minimize the estimation covariance given a desired, pre-specified maximum input-output latency of the feedback control loop.Simulations have been performed that capture the real-time properties of the vision-based tracking algorithm and the effects of the timing on the performance of the control system. The suggested strategy has been compared with heuristic algorithms, and it obtains large improvements in estimation accuracy and performance for objects both in free motion and under closed-loop position control.
AB - In vision-based feedback control systems, the time to obtain sensor information is usually non-negligible, and these systems thereby possess fundamentally different timing behavior compared to standard real-time control applications. For many image-based tracking algorithms, however, it is possible to trade-off the computational time versus the accuracy of the produced position/orientation estimates.This paper presents a method for optimizing the use of computational resources in a multi-camera based positioning system. A simplified equation for the covariance of the position estimation error is calculated, which depends on the set of cameras used and the number of edge detection points in each image. An efficient algorithm for selection of a suitable subset of the available cameras is presented, which attempts to minimize the estimation covariance given a desired, pre-specified maximum input-output latency of the feedback control loop.Simulations have been performed that capture the real-time properties of the vision-based tracking algorithm and the effects of the timing on the performance of the control system. The suggested strategy has been compared with heuristic algorithms, and it obtains large improvements in estimation accuracy and performance for objects both in free motion and under closed-loop position control.
KW - closed-loop position control
KW - heuristic algorithms
KW - estimation covariance
KW - edge detection points
KW - multicamera feedback control
KW - sensor information
KW - real-time control applications
KW - computational resources
KW - position estimation error
KW - multicamera based positioning system
KW - image-based tracking algorithms
KW - vision-based feedback control systems
U2 - 10.1109/RTTAS.2004.1317282
DO - 10.1109/RTTAS.2004.1317282
M3 - Paper in conference proceeding
SN - 0-7695-2148-7
SP - 360
EP - 367
BT - Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS04)
PB - IEEE - Institute of Electrical and Electronics Engineers Inc.
T2 - Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium
Y2 - 25 May 2004 through 28 May 2004
ER -