Perception capabilities of ai robots
- 1. C&T RF Antennas Inc www.ctrfantennas.com www.ctrfantennasinc.com Please Contact us for more information, thank you. Coco Lu coco@ctrfantennasinc.com (+86)13412239096 Perception Capabilities Of AI Robots Now, the perception ability of artificial intelligence robots has achieved significant progress. Around machine vision, robots can realize a series of functions like image recognition, target detection, and text recognition, which are widely used; around natural language processing, robots can perform basic speech understanding, machine translation, voice dialogue, etc.; around machine tactility, robots can realize various actions such as flexible object perception, grasping and pushing. One of the goals of artificial intelligence is to allow computers to simulate human perceptions such as vision, hearing, and touch, and try to see, listen, read, understand images, text, and speech. On this basis, let artificial intelligence have the ability to think, the ability to act will eventually become a human being. Now, the perception ability of artificial intelligence robots has achieved significant progress. Around machine vision, robots can realize a series of functions like image recognition, target detection, and text recognition, which are widely used; around natural language processing, robots can perform basic speech understanding, machine translation, voice dialogue, etc.; around machine tactility, robots can realize various actions such as flexible object perception, grasping and pushing. Single perception or the inability to communicate with each other has become a major reason why current artificial intelligence robots cannot achieve humanoid breakthroughs. In other words, the accuracy, stability, and durability of the robot may far exceed that of humans in terms of a
- 2. C&T RF Antennas Inc www.ctrfantennas.com www.ctrfantennasinc.com Please Contact us for more information, thank you. Coco Lu coco@ctrfantennasinc.com (+86)13412239096 single perception ability and a single job, but once it completes complex tasks in multiple processes, robots are far inferior to human performance. If artificial intelligence robots want to achieve qualitative development, they must achieve multi-modal perception fusion on sensory capabilities. Now in addition to the well-known machine vision, artificial intelligence robots are achieving breakthroughs in machine touch and hearing, and through the perception of vision, touch, and hearing, to greatly enhance the perception of robots. For artificial intelligence robots, ordinary people either have high unrealistic illusions and worry that the robot revolution will come soon, or they have doubts about the universal capabilities of robots and feel that robots can only replace humans in a few scenarios. Machine vision and machine touch As the most intelligent creatures on the planet, 83% of the information acquired by the senses comes from sight, 11% from hearing, 3.5% from the smell, 1.5% from touch, and 1% from the taste. Of these five senses, if unfortunately can only retain one, most of them may retain vision. We must know that most of the nearly 100 billion neurons in our brain are processing visual information. Among all the perceptual information, only dynamic visual information is the most complicated, so that humans have to close their eyes and actively isolate to be called "rest." Because of the importance and complexity of visual information, in the development of artificial intelligence technology, in addition to natural language processing, it is mainly to develop machine vision. This time the wave of artificial intelligence is also revived because of breakthroughs in image recognition. Nowadays, machine vision has blossomed in various fields such as industry, security, daily consumer electronics, and transportation. More and more cameras have AI image recognition capabilities behind them. For most artificial intelligence robots, in addition to visual capabilities, there is also the ability to move, walk, and grasp, which requires the help of touch. For automated robots that often only have a single function, they usually only need to set fixed parameters, moving trajectories, and grasping strength to complete their tasks without sleep. But for artificial intelligence robots, they need to flexibly adapt to objects of different materials, different shapes, and hardness. At this time, both machine vision recognition capabilities and tactile judgments of objects are required. Previously, most robot gripping solutions relied solely on the robot's visual perception. The main solution is to perform image matching through the database, monitor the state of the target object and its own actions in real-time. Finally, adjust the appropriate grasping algorithm to complete the grasp of the object. However, the contact strength of the grasp is machine vision. Irreplaceable, such machines also need tactile sensory data. Just like humans, when we try to grasp objects, we use a combination of various perceptual abilities, the most basic of which is vision and touch. Because vision can cause misjudgments due to factors such as light, shadows, and occlusion of the line of sight, we usually make more effective use of the touch of the skin to obtain a complete perception of objects.
- 3. C&T RF Antennas Inc www.ctrfantennas.com www.ctrfantennasinc.com Please Contact us for more information, thank you. Coco Lu coco@ctrfantennasinc.com (+86)13412239096 The human body's tactile perception is also a very complicated process of bioelectric signal reaction, so to give the machine a tactile ability also requires very complicated processing. To simulate the tactile response of the human body, the robot's tactile sensor must also be able to digitally simulate the texture, smoothness, and shape of the object, and convert the pressure and vibration signals into data signals that can be processed by the computer, so as to train the tactile algorithm. The difficulty of the machine's tactile sense lies in the recognition of small vibrations such as grasping obtained by the tactile sensor. It must be able to recognize the sliding vibration of the grasping object and the vibration generated by the friction between the object and other objects, and it must be able to distinguish the vibration of different objects. These are studies The authors focused on the difficulties they have overcome. The way to achieve a breakthrough is that we need better tactile sensors, and we must achieve better tactile sensors than existing pressure sensors, which can be embedded in flexible materials to realize artificial skin like human skin. Recently, two researchers from the National University of Singapore have developed an artificial skin that is equipped with an artificial brain that can simulate a biological neural network and runs on a neuromorphic processor using Intel Loihi. Based on this technology, the research team passed the test of reading Braille by the robotic arm. At the same time, with the help of visual sensors and this artificial skin, the grasping ability of the robotic arm has also been significantly improved. In the future, robots based on this tactile ability can be more flexible, meticulous, and safe in the item sorting process. In the nursing industry, it can provide better care and assistance to humans, and in surgical robots, better Complete the automation of the operation. The combination of vision and touch can already provide the possibility to improve the perception of robots. Then what effects will the integration of auditory capabilities bring? The complement of machine hearing The machine hearing here does not specifically refer to the recognition of human speech. This type of speech recognition has been widely used in various consumer-grade smart speakers and other fields. The machine hearing here refers to the judgment of sound emitted by all objects through sound sensors. Compared with machine vision's simple and direct judgment of objects, machine hearing is indeed an area that people have been neglecting. In our daily life scenes, in addition to visually judging the distance, color, and size of objects, we usually also use hearing to identify the distance and texture of objects and speculate on the occurrence of events. This is especially important for people with visual impairments. Recently, researchers at Carnegie Mellon University (CMU) discovered that by increasing auditory perception, the perception ability of artificial intelligence robots can be significantly improved. This time, the CMU Robotics Institute conducted a large-scale study of the interaction between sound and robot movements for the first time. Researchers have found that the sounds of different objects can help the robot distinguish objects, such as metal screwdrivers and metal wrenches. Machine hearing can also help robots determine which types of actions produce sound and help them use sound to predict the physical properties of new objects. After testing,
- 4. C&T RF Antennas Inc www.ctrfantennas.com www.ctrfantennasinc.com Please Contact us for more information, thank you. Coco Lu coco@ctrfantennasinc.com (+86)13412239096 the accuracy of the robot in classifying objects through hearing can reach 76%. In order to achieve this test, the researchers used 60 common objects to slide, roll, and impact on a robot tray and recorded 15,000 interactive videos and audios to form a large data set. In addition, researchers can estimate the amount and flow of particulate matter by shaking containers or stirring materials, such as evaluating rice and pasta. Obviously, through the comparison of sounds, many physical properties that cannot be predicted by vision can be predicted. The machine hearing cannot distinguish between a red square and a green square, but it can distinguish two different objects with the sound of impact when it is invisible. And this is where the usefulness of machine hearing lies. In the end, even the researchers were surprised by the effect of voice recognition on objects. In terms of the application of machine hearing, the researchers first thought of adding a cane to the equipment of the robot in the future. The object can be recognized by tapping the cane. This is an interesting picture. However, it is conceivable that machine hearing can play a greater role in future intelligent security, pipeline detection, and body detection. In addition, these applications are more extensive for identifying the most meaningful human voices, such as music and emotions. Application prospects of robot multi-modal perception fusion Just as the importance of sensory organs to human beings, the importance of perception systems to robots is also crucial. You know, we humans rarely use only one sense organ to obtain information and rarely use only one sense organ to guide actions. Just like in a "climb-race-swim" three-in-one competition, we may not be able to defeat monkeys, leopards, and dolphins in a single event, but in the entire game, humans can complete these three events at the same time. When we humans perceive things, we usually have multiple senses at the same time, coordinated and verified multiple times to deepen our perception of external objects. For more complex things, we even have to use rational cognitive abilities such as memory and reasoning to process perceptual things to obtain more complex cognition. Compared with human multi-sensory applications, the robot's single perception or a simple combination of perception capabilities, and because the current robot's perception recognition mode is still based on the analysis and data comparison of the perception data of the algorithm model, it is difficult to generate more complex reasoning Knowledge, therefore, robots are slightly inferior to humans in the complexity of cognition, but far surpass humans in the accuracy and scale of recognizing objects. Now, the advancement of multimodal perception fusion will make robots gradually approach human capabilities in cognitive complexity. In the future, robots will become more comfortable in the face of complex interaction scenarios such as lighting and occlusion, noise and reverberation, motion, and similarity, resulting in various real-world applications with obvious benefits. The possible applications of multimodal perception fusion include: • Specialized precision operation field. For example, in the field of difficult surgical operations, surgical robots can perform more precise surgical operations than surgeons by accurately
- 5. C&T RF Antennas Inc www.ctrfantennas.com www.ctrfantennasinc.com Please Contact us for more information, thank you. Coco Lu coco@ctrfantennasinc.com (+86)13412239096 observing targets and separating and fixing related issues. • High-risk or difficult robot operations. For example, the handling and dismantling of dangerous goods, such as the inspection and repair of difficult areas such as pipelines that ordinary people cannot enter, the handling and salvage of catacombs or objects on the seabed, and sound detection of sealed spaces through machine hearing. Scenes that require flexible handling, such as security, disaster rescue, emergency handling, etc., can be gradually handed over to multi-sensing system robots, or human-machine collaborative remote processing. In addition, due to the improvement of the robot's perception and fusion ability, the robot's training of comprehensive perception data can better understand the complexity of humans, especially the establishment of more complex emotional computing models, which can better understand human expressions, The emotional signals transmitted by sound, skin temperature, and body movements provide new possibilities for more advanced human-computer interaction. At present, artificial intelligence robots are still complex system engineering. To realize the multi-modal perception fusion of robots, comprehensive research on sensor performance, algorithm collaboration, multi-modal tasks, environmental testing, and other aspects are also required. This process must be very difficult, but the future after results must be bright. In the future where we look forward to the harmonious life of humans and robots, we naturally expect that these robots will no longer be a cold machine.