The Harvard RoboBee has long been a marvel of microbotics, capable of flight, diving, and hovering like a real insect. But what good is the miracle of flight without a safe way to land? The RoboBee’s creators have now overcome this hurdle with their most reliable landing gear yet, inspired by nature’s own graceful landers: the crane fly.

Led by Robert Wood, the team has given their flying robot a set of long, jointed legs that help ease its transition from air to ground. This breakthrough protects the delicate piezoelectric actuators – energy-dense “muscles” deployed for flight that are easily fractured by external forces from rough landings and collisions.

The RoboBee’s previous iterations had suffered significant ground effect, or instability as a result of air vortices from its flapping wings. This problem was addressed by Christian Chan, a graduate student who led the mechanical redesign of the robot, and Nak-seung Patrick Hyun, a postdoctoral researcher who led controlled landing tests on a leaf and rigid surfaces.

Their paper describes improvement of the robot’s controller to adapt to ground effects as it approaches, an effort that seeks to minimize velocity before impact and dissipate energy quickly after. This innovation builds upon nature-inspired mechanical upgrades for skillful flight and graceful landing on various terrains.

The team chose the crane fly, a relatively slow-moving and harmless insect that emerges from spring to fall, as their inspiration. They noted its long, jointed appendages that likely give the insects the ability to dampen landings. This design was replicated in prototypes of different leg architectures, settling on designs similar to a crane fly’s.

The success of the RoboBee is a testament to the interface between biology and robotics. Alyssa Hernandez, a postdoctoral researcher with expertise in insect locomotion, notes that this platform can be used as a tool for biological research, producing studies that test biomechanical hypotheses.

Currently, the RoboBee stays tethered to off-board control systems, but the team will continue to focus on scaling up the vehicle and incorporating onboard electronics to give the robot sensor, power, and control autonomy. This three-pronged holy grail would allow the RoboBee platform to truly take off, paving the way for future applications in environmental monitoring, disaster surveillance, and even artificial pollination.

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.

The team of engineers at the University of California San Diego has developed a game-changing robotic gripper made from measuring tape, which could potentially revolutionize fruit and veggie picking. The device, dubbed GRIP-tape, is designed to gently grasp fragile fruits and vegetables, making it an ideal solution for agriculture applications. This low-cost, human-safe robot uses the entire length of the measuring tape as a gripping surface, allowing it to navigate through obstacles and effortlessly pick up objects with different shapes and stiffness.

The gripper’s soft yet robust design enables it to expand and contract, allowing it to reach far and wide without needing additional mechanisms. The team bound two spools of measuring tape together with adhesive to create the perfect configuration for a gripper. Each finger is controlled by four motors that can move independently, giving the robot unparalleled flexibility and precision.

The researchers had previously worked with measuring tape as part of a grant from the National Science Foundation to investigate soft materials that could bend while holding their shape. They discovered that measuring tape was an ideal material due to its springy nature, durability, and thinness, making it perfect for delicate objects.

The gripper’s unique design allows it to rotate objects or act as a conveyor belt, depositing the grasped items into containers with ease. It can pick up a wide range of objects, from small fruits like tomatoes to large ones like lemons, and even navigate through crowded farms with its flexible tape fingers.

Experiments showed that the gripper could easily lift large fruits like fresh lemons, demonstrating its potential for efficient fruit and veggie picking. Next versions of the gripper could improve on the original by adding advanced sensors and AI-driven data analysis, allowing it to operate autonomously and making it an even more valuable tool for farmers.

The work was partially funded by the National Science Foundation, and the team’s innovative design is set to transform the way we harvest crops, making it more efficient, safe, and cost-effective.