Robot experts are no longer limited to manufacturing robots with electric motors, gears, and sensors. They are beginning to experiment with new manufacturing methods such as artificial muscles, soft robot technology, and integrating multiple functions into one material. But most of these advanced manufacturing methods are "one-off" demonstrations, and it is difficult to combine them.

Multifunctional materials that incorporate sensing, movement, energy harvesting, or energy storage can make robot design more efficient. But combining these different attributes on one machine requires the use of new methods that combine microscale and large-scale manufacturing techniques. Another promising research direction is materials that can adapt to the environment or self-heal over time, but this requires more research.

Nature has solved many of the problems that robot experts are trying to solve, so many people turn to biology for inspiration, and are even trying to integrate life systems into their robots. However, there is still a big bottleneck in replicating the mechanical properties of muscles and the ability of biological systems to provide energy themselves.

The artificial muscle has made great progress, but its robustness, efficiency, energy and power density still need to be improved. Embedding live cells into robots can overcome the difficulties of powering small robots, and it can also embed biological features such as self-healing and embedded sensing, but how to integrate these components is still a major challenge. Although more and more "robot animals" are helping humans unlock the secrets of nature, we still have a lot of work to do, such as how animals can switch between abilities such as flying and swimming to help humans build multi-channel platforms.

Energy storage is a major bottleneck for mobile robots. The increasing demand for drones, electric vehicles and renewable energy has promoted the progress of battery technology, but for many years, the fundamental challenges have remained basically unchanged.

This means that while the battery is being developed, it is necessary to try to minimize the electricity demand of the robots and allow them to obtain new energy, so that they can obtain energy from the environment or transfer energy to them wirelessly. Promising research direction.

Groups of simple robots are assembled into different structures to handle different tasks. This may be a cheaper and more flexible solution to replace large robots that perform specific tasks. Smaller, cheaper, and more powerful hardware, combined with artificial intelligence, allows simple robots to perceive the surrounding environment and communicate, thus simulating the behaviors seen in groups of nature.

However, the most effective control method for robot groups of different sizes needs more work, because small groups can be controlled centrally, but large groups need more decentralized control. These robots also need to be made more robust, able to adapt to changes in the real world, and be able to resist intentional or accidental injuries. In addition, more research is needed on non-uniform robot groups with complementary functions.

A key use of robots is to explore places that humans cannot reach, such as deep seas, space, or disaster areas. This means that they need to be good at exploring and navigating in environments where there are no maps, which are often extremely chaotic and dangerous.

Its main challenges include creating systems that can adapt, learn and recover from navigation failures, and be able to explore and identify new discoveries. This requires a high degree of autonomy, allowing the robot to monitor and reset itself, and at the same time to use multiple data sources with different reliability and accuracy to construct an image of the world.

Deep learning has completely changed the ability of machine to recognize patterns, but this needs to be combined with model-based reasoning to create adaptable robots that can learn in the course of work.

The key point here is to create artificial intelligence so that it can realize its limitations and learn how to learn new things. It is also important to create systems that can learn quickly from limited data, rather than the millions of examples required for deep learning. Our further understanding of human intelligence will be the key to solving these problems.

The brain-computer interface will enable seamless control of advanced robotic prostheses, but it also proves a faster and more natural way to communicate instructions to robots, or just help them understand human mental states.

Most current methods of measuring brain activity are extremely expensive and cumbersome, so it will be very important to work on compact, low-power and wireless devices. Due to the inaccuracy of reading brain activity, they also tend to perform extended training, calibration and adaptation. Moreover, whether they will outperform some simpler techniques, such as eye tracking or reading muscle signals, remains to be seen.

If robots are to enter the human life environment, they need to learn to deal with humans. But this is very difficult, because we have almost no specific model of human behavior, and we can easily underestimate the complexity of nature.

Social robots need to be able to perceive subtle social cues such as expressions and intonations, understand their cultural and social background, and model the mental states of people interacting with them to adapt to communication with humans, whether in short-term relationships Still in the process of long-term relationships.

Medicine is one of the areas where robots may have a significant impact in the near future. Robotic devices that enhance surgeon capabilities are already in normal use, but one of the challenges is to increase the autonomy of these systems in such a high-risk environment.

Autonomous robot assistants need to be able to recognize human structures in various scenarios, and be able to use situational awareness and voice commands to understand the needs in different scenarios. In surgical operations, autonomous robots can perform routine steps in the surgical procedure, allowing surgeons to serve patients with more complex conditions.

Micro-robots operating inside the human body are also promising, but there are still many obstacles to using such robots, including effective transmission systems, tracking and control methods, and more importantly, finding treatments that can improve existing methods.

As the previous challenges are overcome, robots will gradually integrate into our lives, but this progress will also create new ethical problems. Most importantly, we may rely too much on robots.

This may cause humans to lose certain skills and abilities and prevent us from controlling the situation in the event of failure. We may eventually delegate tasks that require human supervision to the robot for moral reasons, so that in the event of failure, people will shirk responsibility to the robot. It can also reduce people ’s right to self-determination, because human behavior will change to adapt to the routines and restrictions needed for robots and artificial intelligence to work effectively.

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