Advances in machine vision are causing a seismic shift in the world of robotics. Generation AIbattery life and wireless communication.
6 examples of robots in the real world
- Robot equipped with machine vision
- robot production
- robot avatar
- collaborative robots, i.e. collaborative robots
- self-driving car
- General purpose robotics
Unlike previous products that were limited to repetitive tasks or served as a novelty, modern robot It is poised to become a versatile and intelligent tool in both industrial and personal environments. Machine vision allows you to accurately interpret your environment, and generative AI enables natural language interactions to make commands more intuitive. Enhanced battery life and wireless capabilities make it even more mobile and versatile.
The convergence of technologies is bringing AI to life in the physical world, ushering in a new era in which robots act as effective and intelligent assistants.
machine vision revolution
The power to bring about change machine vision The achievements in the field of robotics and AI cannot be overstated.Machine vision driven by advances in deep learning and Convolutional Neural Network (CNN)is enabling robots to navigate, perceive, and interact with their environments in ways that were previously thought to be the exclusive domain of biological visual systems. The advent of affordable, high-performance GPUs has been a catalyst to provide the computational power needed for real-time vision processing.
This revolution is similar to the Cambrian Explosion in evolutionary history, when the appearance of the eye dramatically expanded the capabilities of living things. Similarly, machine vision is a game-changer for robotics, increasing robot mobility, autonomy, and utility across a variety of applications. Robots can navigate dynamically changing environments, identify and manipulate objects, and even predict where they will be needed, with minimal or no human intervention. Now it looks like this.
Emerging technologies such as single-pixel object detection (SPOD) and optical neural network preprocessors are pushing the boundaries even further. For example, SPOD enables object detection from a single pixel, providing applications from medical image processing to manufacturing quality control. The optical neural network preprocessor achieves incredible compression rates, making real-time processing even more efficient.
Transformer architecture, a new paradigm machine learning, has also expanded into vision tasks, challenging the domain-specific capabilities of CNNs. This indicates a trend toward versatile multitasking models that can handle a variety of sensory inputs and cognitive tasks.
Looking ahead, the integration of onboard and cloud-based intelligence will be the next frontier. Onboard systems manage immediate, time-sensitive tasks, and cloud-based intelligence provides situational understanding and strategic decision-making. However, incorporating safety and security is essential as we embark on this exciting path. ethical guidelines This is to ensure that this newfound autonomy does not introduce unforeseen risks or ethical difficulties.
robot production
Lights-out in factories, where robots handle most of the work with minimal human oversight, has been a long-standing goal in automation (the name comes from the fact that automated production often eliminates the need to turn on the lights). This is due to the fact that While this has been difficult to achieve due to the flexibility of the human workforce, advances in machine vision and learning are making it possible.
Today's robots are versatile, capable of multiple tasks such as sorting, painting, and assembly, and can handle objects of various sizes. This not only increases efficiency but also reduces exposure of people to hazardous situations.
digital twin, real-time virtual replicas of physical systems further optimize operations by enabling predictive analytics and problem solving. This technology has applications outside of manufacturing, such as in medicine.
As the capabilities of robots improve, fully automated factories are becoming more realistic and will require ethical controls to ensure work and safety.
robot avatar
Avatar robots are now more affordable at around $15,000 and have expanded their role beyond performing simple tasks. Equipped with tactile gloves and advanced sensors, users can perform complex tasks remotely. This has applications in fields such as medicine, engineering, and even disaster response. Sharing these avatars between users further extends their usefulness, similar to a ride-sharing model.

These avatars also serve as a rich data source. machine learning. These could help address Moravec's paradox, which highlights the difficulty for machines to master tasks that humans find simple, such as intuitive maneuverability. The rich sensory data and user behavior captured by avatars could provide insights into human behavior beyond what video observation can provide and speed up the development of advanced androids.
This technology also has geopolitical implications.high speed networks such as star link It allows people to work from home around the world without having to relocate, benefiting local communities and increasing the potential for remote working.
As these avatars become more sophisticated, they are likely to evolve from task performers to interactive collaborators, prompting a re-evaluation of AI's social role.
self-driving car
self-driving caris becoming increasingly enabled by affordable LiDAR (light detection and ranging) technology and becoming more common in urban environments. However, the effectiveness of this technology varies depending on factors such as geography, culture, and local laws, making it difficult to implement universally. Remotely controlled avatars bridge the gap towards full autonomy and allow robots to learn from human operators.
Autonomous systems also promise to revolutionize emergency response. They replace riskier and more costly traditional methods such as planes and helicopters in firefighting operations, providing a safer alternative for high-risk drivers and potentially reducing accidents.
But the rise of self-driving cars also raises ethical and social challenges. For example, safer roads could reduce the number of organs available for transplant by 15% due to fewer fatal accidents (Mills and Mills, 2020). In addition, local governments may see less revenue from parking and speeding fines, which often make up a significant part of their budgets (Sibylla, 2019).
General purpose robotics
Advances in machine vision and generative models usher in a new era of general purpose robotics. These robots can understand and execute human language commands, and their applications range from medicine and elderly care to agriculture and warehousing. Robots can also learn from each other and improve their capabilities in various fields.
However, traditional frameworks designed for static systems are not sufficient for these self-learning, adaptive robots. As it continues to evolve, new guidelines must be developed to ensure its ethical and safe operation.
Collaborative robot (cobot)
collaborative robots, i.e. collaborative robots, designed to work safely alongside humans in shared spaces. They are equipped with advanced sensors and controls and are ideal for tasks that require precision, strength, or repetition in fields such as manufacturing, logistics, and medicine. Unlike traditional industrial robots, which are often isolated for safety reasons, collaborative robots have situational awareness and can operate freely among humans.
These robots are especially useful in roles that require fast and precise movements, such as emergency medical response. Although they typically do not collaborate directly with humans on tasks, they play a complementary role, freeing up humans for more complex tasks.
Cobots are already having a huge impact logistics Warehousing, especially sorting and picking operations. As technology matures, their role may expand to tasks such as restocking shelves and, in some cases, replacing semi-skilled workers, thereby improving workplace safety and efficiency.
Excerpt from tame the machine Written by Nell Watson ©2024; Reproduced and adapted with permission from Kogan Page Ltd.