Advancements Essential for Robots to Achieve Self-Governing Capabilities
In the pursuit of true autonomy for robots, it's essential to understand that one breakthrough won't be enough. Instead, progress will come when computation, hardware, materials, and artificial intelligence (AI) advance together.
Currently, robot actuators take 100-500 milliseconds to respond, while human muscles can react in as little as 10-50 milliseconds. To achieve true autonomy, hardware must mimic biological responsiveness. This means developing materials and technology that can respond quickly and efficiently, just like the human body.
Researchers at the University of Greifswald, including Dr. Tahereh Sadat Parvini and Prof. Dr. Markus Münzenberg, are working on neuromorphic processors using magnetic tunnel junctions inspired by the human brain. These processors aim to enable energy-efficient computing, a crucial step towards true autonomy.
International teams like Innatera also develop neuromorphic microcontrollers for AI applications in smart homes, wearables, and the Internet of Things (IoT). These advancements are accelerating robotics autonomy through efficient AI. Meanwhile, spintronics researchers focus on energy-efficient chips for neuromorphic and AI-driven processing.
The Jülich Research Center collaborates internationally on supercomputing infrastructure to support intensive AI and robotics simulations. They use cutting-edge GPU technologies for energy-efficient high performance computing, aiding in the development of true autonomy.
However, the challenge in achieving true autonomy lies in the interdependency of AI models, hardware, manufacturing, and materials. Computation must become neuromorphic and efficient, and AI must move beyond pattern recognition to reasoning and adaptability.
Fleet learning, a technique that allows robots to share experiences and accelerate collective improvement, is another key component. The goal is true autonomy at 20W real-time performance.
Moreover, materials must deliver durability, manufacturability, and repairability for true autonomy. Robots will remain tethered to inefficiency, fragility, and brittleness until these advancements are achieved.
Lastly, cloud-assisted robotics offloads complex planning to cloud systems, further aiding in the journey towards true autonomy. With these interconnected advancements, the future of robotics could see truly autonomous machines that operate seamlessly alongside humans.
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