Editorial Feature

Tackling the Limits of Robot Perception and Sensing

Robots are increasingly used in various industries, including manufacturing, healthcare, and transportation, to perform tasks that are too dangerous, repetitive, or tedious for humans. One key aspect of robotics that has enabled this progress is the ability of robots to perceive and sense their surroundings.

Tackling the Limits of Robot Perception and Sensing

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How Robots Perceive and Sense Their Surroundings 

Robotic perception involves using sensors and other technologies that enable the robot to collect and process data about its environment, including objects, people, and other robots.

The sensory data can come from various sources, such as cameras, lasers, sonar, and tactile sensors. It can be processed using advanced machine learning algorithms to enable the robot to make decisions based on the collected data. By perceiving and sensing their surroundings, robots can operate autonomously and interact with the environment in previously impossible ways.

The Key Technologies in Robotic Perception

Several vital technologies play a crucial role in robot perception. The following technologies enable robots to perceive and interact with their environment effectively:

Computer Vision

Computer vision is a field of artificial intelligence that focuses on enabling computers to interpret and analyze images and videos. Computer vision technologies are used in robots to recognize and identify objects, people, and other things in the environment.

LiDAR (Light Detection and Ranging)

LiDAR sensors use laser light to detect and measure the distance to objects in the environment. Organizations commonly use LiDAR sensors in robots for 3D mapping and obstacle detection.

Radar

Radar is another technology used for object detection and ranging. Radar systems use radio waves to detect objects and can be used to see things beyond the range of LiDAR.

Ultrasonic Sensors

Ultrasonic sensors use high-frequency sound waves to detect the presence of objects and measure distance. Engineers install these sensors in robots to detect objects and avoid obstacles.

Inertial Measurement Units (IMUs)

IMUs combine accelerometers, gyroscopes, and magnetometers to measure the robot's acceleration, orientation, and magnetic field. Robots use IMUs for localization, motion tracking, and gesture recognition.

Global Positioning System (GPS)

GPS technology determines the robot's location and tracks its movement. Robotic system manufacturers often employ GPS technology in outdoor robots, such as drones and autonomous vehicles.

Microphones and Speech Recognition

Microphones and speech recognition technologies are used in robots for human-robot interaction, allowing users to give commands to the robot using natural language.

Why Robots Need Perception

Perception and sensing are critical in enabling robots to interact with their environment meaningfully. Robots use these capabilities to navigate, manipulate objects, interact with humans, and monitor the environment. The robots must be able to perceive their surroundings, detect obstacles, avoid collisions, and follow a predetermined path.

When performing tasks that involve manipulating objects, such as assembly, sorting, and packaging, robots must be able to perceive the object's location, size, and shape to do so effectively.

In scenarios that involve human-robot interaction, robots need to be able to perceive and understand human speech and gestures. To effectively monitor the environment, robot designers develop robots that can sense and measure various parameters of the robot's settings.

Perception and sensing enable robots to perform multiple tasks and applications, making them valuable assets in many industries.

The Limitations of Robotic Perception/Sensing

Robotic perception and sensing have made significant advancements in recent years, but there are still limitations to these technologies that need to be addressed by manufacturers. One of the main challenges is the limited context awareness of robots, which can make it difficult for them to understand the meaning of particular objects or how they relate to the overall scene.

Additionally, some sensing technologies have a limited range, making it difficult for robots to sense far-away objects or environments with poor visibility. Another limitation is the sensitivity of some sensing technologies to changes in lighting or weather conditions, which can impact the accuracy of their readings.

Limited accuracy and high cost are other factors that can hinder the effectiveness of robotic perception. Despite these limitations, ongoing research and development in this field are helping to overcome these constraints and improve the performance and accessibility of robotic perception and sensing technologies.

How Can These Challenges Be Addressed? 

Robotic perception is a crucial area of research in robotics, and there are several ways to address its associated challenges. One approach is to develop new sensing technologies that can improve the accuracy and range of robot perception.

Researchers are continuously working on new LiDAR sensors that can generate more detailed 3D maps of the environment. Another approach is to combine multiple sensing modalities, such as LiDAR, cameras, and radar, to overcome the limitations of individual sensors and improve the robot's perception capabilities.

With advancements in machine learning and artificial intelligence, robots can analyze and process sensing data more effectively, helping to improve accuracy and reduce errors in perception.

Incorporating contextual information into robot perception capabilities, such as using semantic knowledge about objects and their relationships, can help robots better understand the context of their environment. Improving the interaction between robots and their environment, such as actively moving objects to gather more information about their shape and properties, can also enhance perception capabilities.

Additionally, improving the interaction between robots and human users, such as through natural language processing or gesture recognition, can help robots better perceive their environment.

Conclusion

In conclusion, robotic perception is a rapidly developing field that enables robots to sense, understand, and interact with their environments. With advances in sensor technologies, machine learning algorithms, and computing power, robots can now perform various tasks in industrial, medical, and other settings.

Robotic perception offers many benefits, including improved safety, increased efficiency, and reduced costs. However, challenges must be overcome, such as sensor technology limitations, difficulty processing complex sensory data, and issues integrating perception with other robotic capabilities.

Addressing these challenges will require continued investment in research and development and collaboration between experts in various fields. Nevertheless, the potential benefits of robotic perception are enormous, and its continued progress will undoubtedly transform how we interact with and benefit from robotics.

Continue reading: Sensor Systems for Building a Robot

References and Further Reading

Duddala, R. (2022). Robot Perception and Navigation in Challenging Environments. [Online] Fresh Consulting. Available at: https://www.freshconsulting.com/insights/blog/robot-perception-and-navigation-in-challenging-environments/

A, Zewe. (2022). Robot overcomes uncertainty to retrieve buried objects. [Online] MIT News. Available at: https://news.mit.edu/2022/robot-pick-place-hidden-objects-0629

Michael, N. (2020). The Challenges of Robotic Perception. [Online] Shield AI. Available at: https://shield.ai/challenges-robotic-perception/

Amin, G. (2019). How Robots Perceive the World Around Them. [Online] Robotics Business Review. Available at: https://www.roboticsbusinessreview.com/news/how-robots-perceive-the-world-around-them/

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Umar Sajjad

Written by

Umar Sajjad

Umar is a mechatronics and mechanical engineer by trait with a deep interest in Artificial Intelligence, Robotics and Cognitive Science. He is an avid learner with a book always in his hand, always looking for something new to learn. Umar mostly spends his free time involved in sports and fitness with football, hiking and the gym as part of his daily routine.

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