The sinking of the Titanic 113 years ago was a tragic reminder of the importance of accurate navigation. The ship’s encounter with an iceberg led to one of the most infamous maritime disasters in history, and human error likely played a significant role. Today, autonomous systems powered by artificial intelligence (AI) are being developed to help ships avoid such accidents. However, for these systems to be widely adopted, it is crucial that they can provide transparent explanations for their actions.

Researchers from Osaka Metropolitan University’s Graduate School of Engineering have made a significant breakthrough in this area. They have created an explainable AI model specifically designed for ship navigation, which quantifies the collision risk for all vessels in a given area. This feature is particularly important as key sea-lanes have become increasingly congested, making it more challenging to ensure safe passage.

The researchers, Graduate Student Hitoshi Yoshioka and Professor Hirotada Hashimoto, aimed to develop an AI model that not only makes informed decisions but also provides clear explanations for its actions. By using numerical values to express the collision risk, the system can communicate its reasoning to the captain, enabling them to make more informed decisions.

According to Professor Hashimoto, “By being able to explain the basis for the judgments and behavioral intentions of AI-based autonomous ship navigation, I think we can earn the trust of maritime workers. I also believe that this research can contribute to the realization of unmanned ships.”

The findings of this study have been published in Applied Ocean Research, highlighting the potential for explainable AI to improve ship safety and reduce human error. As the maritime industry continues to evolve, the development of transparent and trustworthy autonomous systems will be essential for ensuring safe and efficient navigation.

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Hopping gives this tiny robot a leg up

Insect-scale robots can squeeze into places their larger counterparts can’t, like deep into a collapsed building to search for survivors after an earthquake. However, as they move through the rubble, tiny crawling robots might encounter tall obstacles they can’t climb over or slanted surfaces they will slide down.

To get the best of both locomotion methods, MIT researchers developed a hopping robot that can leap over tall obstacles and jump across slanted or uneven surfaces, while using far less energy than an aerial robot.

The hopping robot, which is smaller than a human thumb and weighs less than a paperclip, has a springy leg that propels it off the ground, and four flapping-wing modules that give it lift and control its orientation.

The robot can jump about 20 centimeters into the air, or four times its height, at a lateral speed of about 30 centimeters per second. It has no trouble hopping across ice, wet surfaces, and uneven soil, or even onto a hovering drone. All the while, the hopping robot consumes about 60 percent less energy than its flying cousin.

Due to its light weight and durability, and the energy efficiency of the hopping process, the robot could carry about 10 times more payload than a similar-sized aerial robot, opening the door to many new applications.

The researchers put the hopping robot, and its control mechanism, to the test on a variety of surfaces, including grass, ice, wet glass, and uneven soil — it successfully traversed all surfaces. The robot could even hop on a surface that was dynamically tilting.

“The robot doesn’t really care about the angle of the surface it is landing on. As long as it doesn’t slip when it strikes the ground, it will be fine,” said Yi-Hsuan (Nemo) Hsiao, an MIT graduate student and co-lead author of a paper on the hopping robot.

Since the controller can handle multiple terrains, the robot can easily transition from one surface to another without missing a beat. For instance, hopping across grass requires more thrust than hopping across glass, since blades of grass cause a damping effect that reduces its jump height.

The researchers showcased its agility by demonstrating acrobatic flips. The featherweight robot could also hop onto an airborne drone without damaging either device, which could be useful in collaborative tasks.

In addition, while the team demonstrated a hopping robot that carried twice its weight, the maximum payload may be much higher. Adding more weight doesn’t hurt the robot’s efficiency. Rather, the efficiency of the spring is the most significant factor that limits how much the robot can carry.

Moving forward, the researchers plan to leverage its ability to carry heavy loads by installing batteries, sensors, and other circuits onto the robot, in the hopes of enabling it to hop autonomously outside the lab.

This research is funded, in part, by the U.S. National Science Foundation and the MIT MISTI program. Chirarattananon was supported by the Research Grants Council of the Hong Kong Special Administrative Region of China. Hsiao is supported by a MathWorks Fellowship, and Kim is supported by a Zakhartchenko Fellowship.

The article begins by highlighting the importance of driving for older adults, particularly in maintaining their independence, quality of life, and cognitive health. However, age-related cognitive decline can impair spatial abilities, leading to reduced driving frequency. New research from the University of East Anglia reveals that over 65s with a poorer sense of direction rely more on GPS navigation systems like Sat Nav or smartphone maps.

The study, which involved 895 UK drivers aged over 65, found that using GPS tended to drive more frequently than those who did not use it. This suggests that the technology helps mitigate against spatial orientation difficulties and maintain driving mobility. The research also showed that older people with a poorer sense of direction rely more on Sat Navs.

Lead author Dr Sol Morrissey noted that using a Sat Nav system can alleviate the cognitive demands of navigation when driving, particularly when visiting less familiar destinations. This technology has become increasingly popular among older drivers.

The team worked with participants to understand how they use GPS and its impact on their driving mobility and cognitive performance. They found that a considerable majority of older drivers use navigation assistance at least for some journeys, commonly for the entire journey to a new destination.

Senior author Prof Michael Hornberger emphasized the importance of understanding factors that keep older people on the roads safely for longer. He noted that supporting older drivers with using GPS navigation could really help maintain their driving independence.

This research was led by UEA in collaboration with several universities and funded by the Department for Transport. The study is supported by the National Institute of Health and Care Research (NIHR) Applied Research Collaboration (ARC) East of England.