Robotics is one of the fastest advancing fields of technology as it has the potential to substitute human input in many fields.
These include surveillance, emergency rescue operations, planetary exploration, patrolling, reconnaissance, entertainment, petrochemical applications, industrial automation, construction, personal services, transportation, medical care, etc.
To unpack some aspects of robotics, today’s blog post shall focus on dissecting the specific vertical of autonomous mobile robots.
What are autonomous robots?
Autonomous robots are essentially robots with the ability to intelligently think and navigate like humans. As such, they don’t need human drivers but their software and the entire system self-pilots.
In layman’s language, this means that such robots can ‘automatically’ make their own decisions and complete specific missions without human intervention via machine learning or AI mechanisms, such as delivering packages, inspecting an area, or manufacturing.
However, not all robots are ‘automatic’ as some need manual intervention either via controls, manoeuvring or decision making.
What are autonomous mobile robots?
Generally speaking, autonomous mobile robots (AMRs) can move without assistance from external human operators in an industrial plant, laboratory, planetary surface, or on a fixed predetermined path.
Such robots possess the ability to determine the actions to be taken to perform a specific task, using an intelligently programmed perception system. AMRs also require a cognition unit or a control system to coordinate all the subsystems that constitute the mobile robot.
Overall, AMRs maintain an array of complex sensors that enable them to comprehend and interpret their environment, which helps them to perform intricate or repetitive tasks in the most efficient manner and path possible, for instance, navigating around fixed obstructions in buildings, or variable obstructions like people, lift trucks, and debris.
Features of autonomous mobile robots
The mechanics of autonomous mobile robotics primarily revolve around four principles.
Locomotion
The locomotive aspect of robotics relates to physical mechanics and kinematics, dynamics, and control theory. While humans have ‘actuators‘ called muscles, that come in different shapes and perform unique functions, like grabbing a cup of coffee or pumping blood.
Autonomous robots are no different from mechanical actuators and motors that convert energy into movement, for example, wheels, linear actuators, or hydraulic ram, etc.
Perception
This feature leverages signal analysis and specialised fields like computer vision and sensor technologies. For humans, perception is mainly performed by our five senses, namely: eyes, ears, skin, hair, and other biological mechanisms that facilitate the process.
For autonomous robots, perception is guided by sensors like laser scanners, stereo vision cameras, bump sensors, force-torque sensors, and even spectrometers that serve as ‘information’ input devices.
These information inputs provide an endless supply of data acting as an ‘Internet of Things’ with a sea of sensors with very long wires reaching back to the mobile robots that might use them.
Cognition
This feature is responsible for intelligently analysing the input data from sensors and ingesting the corresponding actions to accomplish the technical objectives of the autonomous robot.
Cognition features are basically in charge of the control system scheme, which is the “brain” or ‘computer’ of the robot that makes decisions based on its designated mission and any information it receives along the way.
So cognitive mechanisms serve in a manner similar to the neurological system in humans. However, in robots, this ‘neurological’ system is called an embedded system, and operates faster and with higher authority than the computer executing a mission plan and parsing data.
In practice, this is how autonomous mobile robots can decide to halt if they notice an obstacle in their way, or detect a problem.
Navigation
Navigation features help a robot to move in a known or unknown environment while taking into account the technical values of the sensors to achieve the set targets.
This means that the autonomous robot must rely on other elements, like perception (the robot must employ its sensors to obtain valuable data), localisation (the robot must know its present position and configuration), cognition (the robot must basically decide what to do to accomplish its goals), and motion control (the robot calculates its input forces on the actuators to achieve the sought trajectory).
As such, developing navigation mechanisms necessitate knowledge of planning algorithms, information theory, and artificial intelligence.
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