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Robot dexterity intelligence (RDI) is the ability of a robot to manipulate objects with precision and flexibility, using sensors, actuators, and algorithms.[1] It is a challenging task for robots, as they have to deal with the complexity and variability of the real world. Robot dexterity intelligence can enable robots to perform tasks that are too repetitive for humans to get exhausted, such as assembling gadgets, loading dishwashers, or helping elderly people.[2] It is comparable to Artificial General Intelligence (AGI) in a sense that robots will have similar level of dexterity intelligence to humans when it can manipulate objects with precision and flexibility in places where humans work or live. Though humanity are close to AGI thanks to advent of tools such as ChatGPT, Google Bard, Meta's Llama, robots are not agile or efficient at performing physical world tasks. The RDI concept argues that robots will learn by watching humans directly or from videos using deep learning or machine learning quickly.
There are different approaches to achieve robot dexterity intelligence, such as using reinforcement learning, neural networks, or vision-based methods.[3] Some examples of companies that are building robots that can demonstrate high levels of dexterity are:
- Boston Dynamics, a company that creates practical robotics solutions for various domains, such as inspection, site management, warehouse automation, safety and security, and research and development. Some of their robots that have demonstrated high levels of dexterity are Spot, a mobile robot that can walk, climb, and inspect; Stretch, a robot that can streamline case handling and trailer unloading operations; and Atlas, a humanoid robot that can perform acrobatic feats and navigate complex environments.
- Dexterity Inc, a company that introduces intelligent robots for warehouse automation that can pick, move, pack, and collaborate. Their robots use a sense of touch and vision, and the ability to learn and multitask, to handle various tasks such as palletization, depalletization, induction, and truck loading. Their platform does not require a data feed or warehouse software integration, as the robot has a real-time understanding of its environment.
- Dactyl1, a robot hand that learned to flip a toy building block in its fingers using simulation and transfer learning.
- Bi-Touch2, a dual-arm robot that displays tactile sensitivity close to human-level dexterity using AI to inform its actions.
Robot dexterity intelligence is an active area of research that aims to improve the capabilities and applications of robots in various domains. It is also a fascinating topic for human curiosity and imagination.
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