In a recent study published in Applied Sciences, Chinese researchers developed an advanced version of the YOLOv8 model, named YOLOv8n, to enhance the accuracy of road pattern recognition for vision-guided robots.
Image sensors face substantial challenges when dealing with dynamic, diverse and unpredictable scenes in open-world applications. However, the development of image sensors towards high speed, high resolution, large dynamic range and high precision is limited by power and bandwidth. Here we present a complementary sensing paradigm inspired by the human visual system that involves parsing visual information into primitive-based representations and assembling these primitives to form two complementary vision pathways: a cognition-oriented pathway for accurate cognition and an action-oriented pathway for rapid response. To realize this paradigm, a vision chip called Tianmouc is developed, incorporating a hybrid pixel array and a parallel-and-heterogeneous readout architecture. Leveraging the characteristics of the complementary vision pathway, Tianmouc achieves high-speed sensing of up to 10,000 fps, a dynamic range of 130 dB and an advanced figure of merit in terms of spatial
A recent study in Robotics introduced an intelligent hybrid task planner for multi-robot disassembly of electric vehicle (EV) lithium-ion batteries. This system, tested with various trajectory-planning algorithms, demonstrated efficient and adaptable collaboration between robots, streamlining the battery recycling process and highlighting its potential for broader disassembly tasks in the circular economy.
Artificial intelligence (AI) finds its way into almost every aspect of Americans' lives. At the end of February, there was a minor scandal regarding fast food burger giant Wendy's tests with software-generated dynamic pricing in
Artificial intelligence (AI) finds its way into almost every aspect of Americans’ lives. At the end of February, there was a minor scandal regarding fast food burger giant Wendy’s tests