Researchers create aerially transforming morphobot ATMO to address complex aerodynamic forces near ground level. The system uses advanced control method model predictive control to adapt quickly to changing dynamics during transformation.
Researchers develop active metamaterials that can autonomously roll, crawl, and wiggle over unpredictable terrain, including uphill and obstacles. These 'odd' objects achieve motion through unusual interactions between motorized building blocks, demonstrating decentralized and robust locomotion.
Researchers used small wheeled robots to study indirect mechanical interactions on deformable surfaces, finding that active matter can interact through non-contact forces. They created a model to control collective behavior by modifying robot design, mirroring celestial bodies' paths in Einstein's General Relativity.
Researchers have developed a new model, Dynamic Resistive Force Theory (DRFT), to predict the locomotion performance of vehicles and other objects in granular media. The model captures diverse counterintuitive observations in granular locomotion, including behaviors seen in circular and 'grousered' wheel locomotion.