As robots become more common in industrial applications and other aspects of everyday life, sophisticated control systems have never been more crucial.
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Robots have become an intricate part of our lives and industry, performing the kind of heavy lifting that would have previously required a great deal of manpower as well as automating production lines allowing manufacturing to become large scale. Additionally, robots are increasingly being tasked with more delicate roles too sensitive for human workers.
For example, robots are now regularly called upon to perform surgery which the Mayo Clinic¹ says allows doctors to perform many types of complex procedures with more precision, flexibility, and control than is possible with conventional techniques as well as being less invasive.
The most common clinical robot system used in surgeries is a mechanical arm equipped with surgical instruments and a camera controlled by a nearby surgeon who has a 3D view of the surgical site.
However, surgery is not the only place that robots can be encountered in medicine.
Such systems also assisting in research laboratories where they are used to automate manual, repetitive, and high-volume tasks, and even in patient care, helping health care workers minimize contact with pathogens — something that has become particularly important during the SARS-CoV-2 (COVID-19) pandemic.
Furthermore, health is not the only area in which delicate and careful robotic control is required; robots are now helping in materials applications handling everything from primers to plasma. Increasingly, a single robot can also be used for a multitude of tasks, no longer restricted to a single repetitive and menial labor.
All the above intricate tasks have required vast improvements in robotic technology, particularly in one area; control.
What is Robot Motion Control?
Medical Design Briefs² defines robot motion control as a system that enables articulated arms to move through the action of rotating and sliding joints, and in guiding mobile robots to move through locomotion and steering. This enables controlled tasks that can be manipulative — such as the use of a gripper — or sensory — positioning and capturing visual data with a camera.
Designing such a system requires controlling things like speed, position, and torque. Even the number of degrees of freedom — the number of ways it can move — possessed by a robot needs to be considered when it comes to motion control.
A robot that has extra joints not required for a task may be more difficult to control but can also add a degree of flexibility to the performance of that task by allowing for a multitude of approaches to be adopted. But, this flexibility — which would require a great deal of brainpower for a human — consumes a lot of computing power for a robot.
Amongst things that need to be considered are factors for a smooth movement like collision avoidance, workspace limits, and even ensuring the overlap of joints does not occur and the joint limits and movement speeds are respected.
There are also other considerations in robot motion control, such as the speed of a task and the amount of power that would be consumed by a specific approach.
To address these challenges, Medical Design Briefs points out that mathematical approaches have been developed. One particular mathematical tool highlighted is the Jacobian matrix which sidesteps direct calculations of positions and can solve control problems with its simplified form.
The Jacobian matrix is an example of one type of control mechanism — local control — with issues common to this kind of system.
Global and Local Robot Control
While local control systems like the Jacobian matrix have some advantages, some challenges in Robot Motion Control require a global approach.
The difference between the two forms of control systems is that local control is best suited to small and well-defined movements. Global control starts with set endpoints calculating a flexible path consisting of large movements in-between these points.
Of course, whether users select local or global controls depend on the type of task the robot is assigned to and the environment in which it is operating. Yet, these different control schemes aren’t mutually exclusive. Robots can be optimized by using a combination of local and global control.
Designers of robotic systems have a wide range of both open-source and commercial software available to them when it comes to selecting a motion control system. This software can eliminate the years of development time that it takes to create a specialized motion-control platform.
Automation News & Resources³ points out that the huge variety of different types of software available for robot motion control and path planning can lead to developers becoming overwhelmed.
A major aspect of robot control is path planning, but again there are two significant approaches to moving a robot from A to B. To ensure a robot controls for aspects like vibration and jerk by controlling joint position task paths are often generated offline before motion is underway.
Specific offline programming software exists and simulator and mobile robot planning software can be used to account for the complexities of real-world environments and operating spaces.
The only issue with this approach is a recalculated path fails to take into account changes that can occur as a task is underway. That means to account for changes in the environment and the actions of the user, a slower and more cautious “real-time” approach to robot motion control may sometime be needed.
Real-time path planning is more complex than the preplanning approach of offline software as it requires continually updating in response to changes in the environment.
Automation News & Resources adds that while artificial intelligence (AI) programs have always been associated with robot motion control, this is now a growing trend in robot control.
Like all motion control platforms, AI is suited to very specific situations and environments, meaning robot developers must be cognizant of their specific requirements and challenges before selecting a control software.
References and Further Reading
¹ Robotic surgery, Mayo Clinic, https://www.mayoclinic.org/tests-procedures/robotic-surgery/about/pac-20394974
² Robotics Motion Control: The Complex Relationship Between Movement and Task, Medical Design Briefs, [https://www.medicaldesignbriefs.com/component/content/article/mdb/pub/briefs/34808]
³ 9 Types of Robotics Software You Might Consider for Your Robot, Automation News & Resources, [https://www.automate.org/]
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