Multisensor Data Fusion for Reliable Obstacle Avoidance

In this work, we propose a new approach that combines data from multiple sensors for reliable obstacle avoidance. The sensors include two depth cameras and a LiDAR arranged so that they can capture the whole 3D area in front of the robot and a 2D slide around it. To fuse the data from these sensors, we first use an external camera as a reference to combine data from two depth cameras. A projection technique is then introduced to convert the 3D point cloud data of the cameras to its 2D correspondence. An obstacle avoidance algorithm is then developed based on the dynamic window approach. A number of experiments have been conducted to evaluate our proposed approach. The results show that the robot can effectively avoid static and dynamic obstacles of different shapes and sizes in different environments.Comment: In the 11th International Conference on Control, Automation and Information Sciences (ICCAIS 2022), Hanoi, Vietna

Aetiologies of central nervous system infection in Viet Nam: a prospective provincial hospital-based descriptive surveillance study.

Infectious diseases of the central nervous system (CNS) remain common and life-threatening, especially in developing countries. Knowledge of the aetiological agents responsible for these infections is essential to guide empiric therapy and develop a rational public health policy. To date most data has come from patients admitted to tertiary referral hospitals in Asia and there is limited aetiological data at the provincial hospital level where most patients are seen.We conducted a prospective Provincial Hospital-based descriptive surveillance study in adults and children at thirteen hospitals in central and southern Viet Nam between August 2007-April 2010. The pathogens of CNS infection were confirmed in CSF and blood samples by using classical microbiology, molecular diagnostics and serology.We recruited 1241 patients with clinically suspected infection of the CNS. An aetiological agent was identified in 640/1241 (52%) of the patients. The most common pathogens were Streptococcus suis serotype 2 in patients older than 14 years of age (147/617, 24%) and Japanese encephalitis virus in patients less than 14 years old (142/624, 23%). Mycobacterium tuberculosis was confirmed in 34/617 (6%) adult patients and 11/624 (2%) paediatric patients. The acute case fatality rate (CFR) during hospital admission was 73/617 (12%) in adults and to 42/624 (7%) in children.Zoonotic bacterial and viral pathogens are the most common causes of CNS infection in adults and children in Viet Nam