Stay informed with a selection of top articles ranging from daily news and career advice to monthly updates on AI, sustainability, software, and more by subscribing to our newsletter. Receive expert insights, exclusive content, and delve deeper into engineering and innovation with fewer ads or enjoy a completely ad-free experience. Join us at IE Media, Inc. and follow our journey.
A group of researchers has made a breakthrough in soft robotics by developing a system that enables robots to sense touch and movement without the need for cameras or external tracking devices. By focusing on proprioception, known as the body’s “sixth sense,” similar to how humans understand body position and movement without visual cues, the team created an “expected perception” framework for the soft robots. This framework allows the robots to predict their body movements, compare them with real-time sensory feedback, and detect external contact or environmental interactions.
The researchers equipped a flexible robot with liquid-metal-based sensors capable of measuring bending, strain, and deformation. Through internal sensing, the robot was able to navigate and respond to physical interactions in real time. Professor Cecilia Laschi from the National University of Singapore emphasized the importance of proprioception in soft robots, addressing the challenge of distinguishing between their own movements and external forces efficiently.
In experimental tests, the robot autonomously navigated a maze using touch and internal sensing, demonstrating the ability to detect walls and adjust its path without the use of cameras. Additionally, the robot successfully mimicked movements guided by a human operator with high precision, showcasing the potential applications in healthcare, rehabilitation, and assistive robotics.
The innovative technology could enhance human-robot interactions, benefiting various fields such as healthcare and underwater robotics. By leveraging touch-based perception, these advanced soft robots could assist elderly individuals, support caregivers, or aid surgeons during minimally invasive procedures. The interdisciplinary nature of robotics, combining neuroscience, material science, artificial intelligence, and biology, is key to shaping future robotic systems.
The researchers aim to further enhance the system through machine learning models inspired by human brain functioning, as they published their findings in Nature Communications. Neetika Walter, a seasoned journalist with a background in politics, business, technology, and clean energy, lent her insight to this compelling story. With a passion for contemporary culture, literature, and storytelling, Neetika’s writing brings depth and perspective to her work. In her leisure time, she enjoys reading books and spending time with her dogs.
