By watching their own motions with a camera, robots can teach themselves about the structure of their own bodies and how they move, a new study by researchers at Columbia Engineering now reveals. Equipped with this knowledge, the robots could not only plan their own actions, but also overcome damage to their bodies.
Humanoid robots, which have a body structure that mirrors that of humans, could rapidly and effectively tackle a wide range of tasks in real-world settings. These robots and their underlying control algorithms have improved considerably in recent years. Many of them can now move faster, emulating various human-like movements.
Researchers from the Shenyang Institute of Automation of the Chinese Academy of Sciences have developed a multi-mode swimming soft robotic fish. Drawing inspiration from the highly sensitive lateral line sensing system and advanced muscle actuation mechanisms of natural fish, the new design integrates actuation, perception, and control capabilities, offering significant advancements in underwater robotics.
Researchers have engineered groups of robots that behave as smart materials with tunable shape and strength, mimicking living systems. "We've figured out a way for robots to behave more like a material," said Matthew Devlin, a former doctoral researcher in the lab of University of California, Santa Barbara (USCB) mechanical engineering professor Elliot Hawkes, and the lead author of the article published in the journal Science.
In recent years, roboticists and computer scientists have developed a wide range of systems inspired by nature, particularly by humans and animals. By reproducing animal movements and behaviors, these robots could navigate real-world environments more effectively.
Humans are known to accumulate knowledge over time, which in turn allows them to continuously improve their abilities and skills. This capability, known as lifelong learning, has so far proved difficult to replicate in artificial intelligence (AI) and robotics systems.
Swimming robots play a crucial role in mapping pollution, studying aquatic ecosystems, and monitoring water quality in sensitive areas such as coral reefs or lake shores. However, many devices rely on noisy propellers, which can disturb or harm wildlife. The natural clutter in these environments—including plants, animals, and debris—also poses a challenge to robotic swimmers.
A recent breakthrough in photothermal actuator design has been achieved by a research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, led by Prof. Tian Xingyou and Prof. Zhang Xian. The team developed a novel superstructure liquid metal/low expansion polyimide/polydimethylsiloxane (LM@PI/PDMS) actuator, which combines rapid movement with impressive load-carrying capacity—an achievement that has eluded previous actuator designs.
The ballbot is a unique kind of robot with great mobility and possesses the ability to go in all directions. Obviously, controlling such a robotic device must be tricky. Indeed, ballbot systems pose unique challenges, particularly in the form of the difficulty of maintaining balance and stability in dynamic and uncertain environments.
Conventional drones use visual sensors for navigation. However, environmental conditions like dampness, low light, and dust can hinder their effectiveness, limiting their use in disaster-stricken areas. Researchers from Japan have developed a novel bio-hybrid drone by combining robotic elements with odor-sensing antennae from silkworm moths. Their innovation, which integrates the agility and precision of robots with biological sensory mechanisms, can enhance the applicability of drones in navigation, gas sensing, and disaster response.
An innovative circuit design could enable miniature devices, such as microdrones and other microrobotics, to be powered for longer periods of time while staying lightweight and compact. Researchers from the University of California San Diego and CEA-Leti developed a novel self-sustaining circuit configuration—featuring miniaturized solid-state batteries—that combines high energy density with an ultra lightweight design.
Soft robotics is an emerging field in the robotic world with promising adaptability in navigating unstructured environments. Where traditional robots struggle with unpredictable terrains, soft robots are advancing in their navigational skills due to their high-end flexibility.
A new study shows an application of machine-learning directed optimization (ML-DO) that efficiently searches for high-performance design configurations in the context of biohybrid robots. Applying a machine learning approach, the researchers created mini biohybrid rays made of cardiomyocytes (heart muscle cells) and rubber with a wingspan of about 10 mm that are approximately two times more efficient at swimming than those recently developed under a conventional biomimetic approach.
A team of researchers from the University of Science and Technology of China (USTC) has recently developed a lightweight prosthetic hand with 19 degrees of freedom (DOF), capable of replicating human hand functions. This development can assist in the functional rehabilitation and daily activities of millions of upper-limb amputees. The research was published in Nature Communications.
From disaster zones to extreme environments, there remain areas difficult for even humans to reliably access. This poses a problem for search-and-rescue operations, research, surveillance, and more. Now, however, a research team from Osaka University and Diponegoro University, Indonesia is hard at work on one potential solution: the cyborg insect.