Tham khảo tài liệu 'dynamic vision for perception and control of motion - ernst d. dickmanns part 12', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Theoretical Background 315 with ọ13 ÓT-1 e aT a2 p23 1 -e aT a ọ33 e aTfor colored noise for white noise these terms are 913 T 2 2 923 T 933 1 In tests it has been found advantageous not to estimate the shape parameters and distance separately but in a single seventh-order system the symmetry of the crossroad boundaries measured by edge features tends to stabilize the estimation process xk 1 f 1 T 913 0 0 0 0 lCR 913 qi 0 1 923 0 0 0 0 lCR 923 q 1 0 0 933 0 0 0 0 lCR 933 qi 0 0 0 1 T 0 0 bCS T qb 0 0 0 0 1 0 0 bCS qb 0 0 0 0 0 1 T 9cr T q 10 0 0 0 0 0 17 9 CR k . J k The last vector noise term allows determining the covariance matrix Q of the system. The variance of the noise signal is ơ E q - q E q for q 0. Assuming that the noise processes ql qb and q1v are uncorrelated the covariance matrix needed for recursive estimation is given by Equation . The standard deviations ƠI ơb and have been determined by experiments with the real vehicle the values finally adopted for VaMoRs were Ơ1 ơb and G . . Q E q qT 2 2 913 02 913 923 O 2 913 933 02 0 0 0 923 913 02 2 1 923 i 923 933 02 0 0 0 0 933 913 O 2 933 923 02 2 _2 933 02 0 0 0 0 . 0 0 0 T2 ob T 02 0 0 0 0 0 T ob 02 0 0 0 0 0 0 0 T2 02 T 0 0 0 0 0 T Measurement model Velocity measured conventionally is used for the vision process since it determines the shift in vehicle position from frame to frame with little uncertainty. The vertical edge feature position in the image is measured the one-dimensional measurement result thus is the coordinate zB. The vector of measurement data therefore is y _ V ZB 0 ZB1 ZB 2 ZBi ZBm . The predicted image coordinates follow from forward perspective projection based on the actual best estimates of the state components and parameters. The partial derivatives with respect to the unknown variables yield the elements of the Jacobian matrix C see Section 316 10 Perception of Crossroads C ổy ổx . The detailed derivation is given in .
