Ocean currents pose a significant challenge in the path planning of autonomous underwater vehicles (AUVs), with conventional path-planning algorithms often failing to effectively counter these influences. In response to this challenge, we propose a path-planning algorithm that can consider the influences and constraints of ocean currents, which leverages the strengths of two widely employed path-planning algorithms, A* and the genetic algorithm (GA), to account for the influences of ocean currents on the planned paths. Specifically, it enhances the initial population generation, formulates a fitness function tailored to ocean current conditions, and employs an adaptive mutation approach to enhance population diversity and stability. By utilizing simulated and real-world ocean current datasets, we validated the feasibility of the proposed algorithm with quantitative metrics. The results demonstrate that in comparison to conventional methods, the new algorithm can deal with the influences and constraints of ocean currents in AUV path planning, resulting in notable enhancements in path smoothness, energy efficiency, and safety.

Simulation platforms are critical and indispensable tools for application developments of unmanned aerial vehicles (UAVs) because the UAVs are generally costly, have certain requirements for the test environment, and need professional licensed operators. Thus, developers prefer (or have) to test their applications on simulation platforms before implementing them on real machines. In the past decades, a considerable number of simulation platforms for robots have been developed, which brings convenience to developers, but also makes them hard to choose a proper one as they are not always familiar with all the features of platforms. To alleviate this dilemma, this paper provides a survey of open-source simulation platforms and employs the simulation of a multi-copter UAV swarm as an example. The survey covers seven widely used simulators, including Webots, Gazebo, CoppeliaSim, ARGoS, MRDS, MORSE, and USARSim. The paper outlines the requirements for multi-copter UAV swarms and shows how to select an appropriate platform. Additionally, the paper presents a case study of a UAV swarm based on Webots. This research will be beneficial to researchers, developers, educators, and engineers who seek suitable simulation platforms for application development, (not only multi-copter UAV swarms but also other types of robots), which further helps them to save expenses for testing, and speed up development progress.

To investigate dynamic change of cadmium body burden and renal dysfunction among residents living in cadmium-polluted areas. From April to July of 2011, the cadmium-polluted areas of northern Guangdong province in China was chosen as the study site. Based on the levels of cadmium pollution in soil and rice, the survey areas were divided into low exposed group (average concentration of cadmium was 0.15-0.40 mg/kg, 0.5-1.0 mg/kg in rice and soil, respectively) and high exposed group (average concentration of cadmium was >0.40 mg/kg, >1.0 mg/kg in rice and soil, respectively). Stratified random sampling and cluster sampling method of epidemiological investigations were carried out among 414 local residents who lived in cadmium exposure areas for more than 15 years, aged above 40, and without occupational cadmium exposure, including 168 and 246 residents in low and high exposed group, respectively. From March to June of 2014, 305 respondents of those who participated in 2011 were successfully traced, including 116 and 189 respondents in low and high exposed group, respectively. We used health questionnaires to acquire their health status. Home-harvested rice and vegetable samples were collected using quartering method for detection of cadmium level, including 190 rice samples, 161 vegetable samples in 2011 and 190 rice samples, 153 vegetable samples in 2014. Urine specimens of residents were collected for the detection of urinary cadmium and creatinine as well as renal dysfunction biomarkers, namely, N-acetyl-beta-D-glucosamidase (NAG) and β2-microglobulin (β2-MG), respectively. In 2011 and 2014, Chi-square test was used to investigate the differences of abnormality of cadmium concentration in rice, vegetables and urinary cadmium, β2-MG, and NAG that were expressed as odds ratio(OR) and 95% confidence intervals (95%CI). In 2011 and 2014, cadmium concentration P50 (P25-P75) in rice was 0.43 (0.17-1.10) mg/kg, and 0.42 (0.20-1.14) mg/kg, respectively (Z=-0.77,P=0.440). In 2011 and 2014, cadmium concentrations P50 (P25-P75) in vegetables were 0.13 (0.07-0.34) mg/kg, and 0.25(0.12-0.59) mg/kg, respectively, with abnormal rates of 38.5%(62/161) and 60.8%(93/153), respectively. In 2014, both average concentration and abnormal rate of cadmium in vegetables were higher than those in 2011 (Z=-4.69, P<0.001 and χ(2)=15.58,P<0.001). Concentrations of urinary cadmium P50 (P25-P75) in high exposed group were 7.90 (3.96-14.91) μg/g creatinine, 8.64 (4.56-17.60) μg/g creatinine in 2011 and 2014, respectively. Contrary to that in 2011, urinary cadmium of high exposed group was significantly increased in 2014 (Z=-2.80, P=0.005). In 2011 and 2014, concentrations of β2-MG, NAG P50 (P25-P75) were 0.15(0.07-0.29) μg/g creatinine, 0.15 (0.07-0.45) μg/g creatinine, and 7.12 (5.05-10.65) U/g creatinine, 13.55(9.1-19.84) U/g creatinine, respectively, with abnormal rates of 7.5% (23/305), 15.1% (46/305), 8.2% (25/305) , and 33.8% (103/305), respectively. Compared with baseline in 2011, average concentrations of β2-MG, NAG significantly increased in 2014 (Z=-2.263, P=0.024 and Z=-12.52, P<0.001), and abnormal rates of β2-MG, NAG were also higher in 2014 (χ(2)=15.61 , P<0.001 and χ(2)=64.72, P<0.001), with odds ratio(OR) of 2.00 (95%CI:1.23-3.24) and 4.12 (95%CI:2.87-5.92). Environmental cadmium pollution of crops such as rice and vegetables in survey areas continued to remain high. Body burden of cadmium might kept at sustainably high levels and renal dysfunction was worsened after continuous, long-term cadmium exposure. Our results suggested that NAG might be more sensitive than β2-MG to serve as an indicator for an individual's future tubular function.

To address unclear multi-constraint coupling mechanisms, energy estimation errors, and poor dynamic feasibility in autonomous underwater vehicle path planning, this paper proposes an energy-efficient velocity-kinodynamic rapidly exploring random tree star algorithm. The method integrates a velocity–energy model, a velocity–curvature model, and a velocity–safe-distance model into a planning framework. Four targeted improvements are incorporated: a potential-field-guided sampling, an adaptive step-length expansion, a kinodynamic feasibility constraint, and a multi-objective cost function. Simulation experiments across four scenarios and five start–goal tasks show that the proposed method eliminates all curvature violations, reduces propulsion energy by up to 49.4% and improves mean minimum obstacle clearance by 34.2% and 47.4% over the two baselines. Ablation studies confirm that each module contributes to overall performance.