Bridging GNSS Outages with IMU and Odometry: A Case Study for Agricultural Vehicles.

Nowadays, many precision farming applications rely on the use of GNSS-RTK. However, when it comes to autonomous agricultural vehicles, GNSS cannot be used as a stand-alone system for positioning. To ensure high availability and robustness of the positioning solution, GNSS-RTK must be fused with additional sensors. This paper presents a novel sensor fusion algorithm tailored to tracked agricultural vehicles. GNSS-RTK, an IMU and wheel speed sensors are fused in an error-state Kalman filter to estimate position and attitude of the vehicle. An odometry model for tracked vehicles is introduced which is used to propagate the filter state. By using both IMU and wheel speed sensors, specific motion characteristics of tracked vehicles such as slippage can be included in the dynamic model. The presented sensor fusion algorithm is tested at a composting site using a tracked compost turner. The sensor measurements are recorded using the Robot Operating System (ROS). To analyze the achievable accuracies for position and attitude of the vehicle, a precise reference trajectory is measured using two robotic total stations. The resulting trajectory of the error-state filter is then compared to the reference trajectory. To analyze how well the proposed error-state filter is suited to bridge GNSS outages, GNSS outages of 30 s are simulated in post-processing. During these outages, the vehicle's state is propagated using the wheel speed sensors, IMU, and the dynamic model for tracked vehicles. The results show that after 30 s of GNSS outage, the estimated horizontal position of the vehicle still has a sub-decimetre accuracy.

Integrated imaging using MRI and 123I metaiodobenzylguanidine scintigraphy to improve sensitivity and specificity in the diagnosis of pediatric neuroblastoma.

OBJECTIVE: The objectives of this study were to compare MRI and iodine-123 ((123)I) metaiodobenzylguanidine (MIBG) scintigraphy in the detection of neuroblastoma lesions in pediatric patients and to assess the additional value of combined imaging. MATERIALS AND METHODS: Fifty MRI and 50 (123)I MIBG examinations (mean interval, 6.4 days) were analyzed retrospectively with regard to suspected or proven neuroblastoma lesions (n = 193) in 28 patients. MRI and MIBG scans were reviewed by two independent observers each. Separate and combined analyses of MRI and MIBG scintigraphy were compared with clinical and histologic findings. RESULTS: With regard to the diagnosis of neuroblastoma lesion, MIBG scintigraphy, MRI, and combined analysis showed a sensitivity of 69%, 86%, and 99% and a specificity of 85%, 77%, and 95%, respectively. On MRI, 15 false-positive findings were recorded: posttherapeutic reactive changes (n = 10), benign adrenal tumors (n = 3), and enlarged lymph nodes (n = 2). On MIBG scintigraphy, 10 false-positive findings occurred: ganglioneuromas (n = 2), benign liver tumors (n = 2), and physiologic uptake (n = 6). Thirteen neuroblastoma metastases and two residual masses under treatment with chemotherapy were judged to be false-negative findings on MRI. Two primary or residual neuroblastomas and one orbital metastasis were misinterpreted as Wilms' tumor, reactive changes after surgery, and rhabdomyosarcoma on MRI. Thirty-two bone metastases, six other neuroblastoma metastases, and one adrenal neuroblastoma showed no MIBG uptake. On combined imaging, one false-negative (bone metastasis) and three false-positive (two ganglioneuromas and one pheochromocytoma) findings remained. CONCLUSION: In the assessment of neuroblastoma lesions in pediatric patients, MRI showed a higher sensitivity and MIBG scintigraphy a higher specificity. However, integrated imaging showed an increase in both sensitivity and specificity.