Robotic manipulation and motion planning are two key aspects of control engineering that can enhance the quality and efficiency of manufactured products. In this article, you will learn what these concepts are, how they work, and what benefits they can bring to different industries and applications.
Robotic manipulation is the process of controlling the movement and interaction of a robot's end-effector, such as a gripper, a tool, or a sensor, with its environment. It involves planning and executing motions that achieve a desired goal, such as grasping an object, assembling a part, or inspecting a surface. Robotic manipulation requires a combination of sensors, actuators, algorithms, and feedback mechanisms to perform complex and precise tasks.
As we progress from Industry 4.0 to 5.0, robotic manipulation is ever so more important. Not only in crash detection mode for other tooling/equipment, but with a higher priority to human-interface safety. In recent decades, the amazing advances made in camera and similar vision systems, had propelled robotic manipulation to the next level.
Moving tools, instruments and parts is the primary function of an industrial robot. If they did not need to move, no robot would be needed. There are a few applications where the robot applies force instead of motion to perform the work, but this is far less common and carrying tools/instruments/parts and interfacing with other stationary or moving objects.
Motion planning is the process of finding a feasible and optimal path for a robot or a part of a robot to move from one configuration to another, while avoiding obstacles and satisfying constraints. It involves generating and evaluating possible trajectories that account for the robot's kinematics, dynamics, geometry, and environment. Motion planning can be applied to different levels of abstraction, such as joint space, task space, or workspace.
The easiest way to fully concider and comprehend what motion planning is, can be by relating how the automotive industry had been stadily forging ahead with autonomous driving in the last 15-20 years. The autonomous driving system utilizes a combined mixture of complex logarithms, sensors, coordinate GPS systems, cameras, etc. They all interface and work together in a theory of constraints cyber framework, that reduces the probability of undesired movements.
Motion planning can help to select the best robot(s) and related machinery, equipment, and tooling, optimize sequence of operation, time cycles, robot loads, cell configuration, and part quality. Planning can run interative sequences or paths far more quickly than can physically be done, and in advance of the cell being completed and ready for launch. This can not only save launch time, but far more importantly, help achieve optimal production rates, costs, and quality.
Robotic manipulation and motion planning are important for manufacturing because they can improve the quality, efficiency, and flexibility of production processes. By using robots that can manipulate and move objects with high accuracy, speed, and reliability, manufacturers can reduce errors, waste, and downtime, as well as increase productivity, safety, and customer satisfaction. Moreover, by using robots that can adapt to changing scenarios, such as different products, layouts, or demands, manufacturers can enhance their innovation, competitiveness, and responsiveness.
One of the key overlooked macro reason for the usage of robotic manipulation, is cost. In the open market, cost is the primary force in mindest change and ultimately manufacturing process' change and/or enhancements. After initial investment, the ROI is based off of many factors: - increased productivity - decreased costly quality issues - more robust and repeatable products - full traceability of components and process window - less downtime and more accurate preventative maintenance (PM) due to continuous feedback loops.
Without conventional 6 axis robots, humans or hard automation would need to do the work, which could be unsafe or cause ergonomic or mental strains from repetitive motions. Prior to Robotics becoming available, any automated equipment was installed, tested, and then put into production and left running that way without any improvement for the life of the program. With Robotics, continuous improvement is far easier and likely to be done.
Robotic manipulation and motion planning are implemented in practice by using various methods and tools that depend on the specific application and requirements. These include kinematic and dynamic models to describe motion and forces, sensor fusion to combine data from different sources, planning algorithms to search for feasible and optimal paths, control algorithms to execute the planned paths, as well as simulation and testing tools to verify and validate the performance of the robot. All of these methods are necessary for a successful implementation.
Implementation of robotic manipulation and planning is best executed with a diverse, cross-functional team that have experience and expertise in their field. As this is a relatively new introduction into manufacturing that can currently be made with mainly OEM's due to the high capital investment, for medium to smaller companies it is best to utilize third party companies that are specialized in this area.
Robotic manipulation and motion planning are applied to a variety of industries and domains, such as automotive, healthcare, agriculture, aerospace, and consumer goods. For example, robots can manipulate and move parts and assemblies in automotive for welding, painting, inspection, or repair; instruments and devices in healthcare for surgery, rehabilitation, or diagnosis; crops and products in agriculture for harvesting, sorting, or packaging; components and structures in aerospace for assembly, maintenance, or inspection; and products and materials in consumer goods for sewing, printing, or personalization.
There are currently no industries that are not pursuing robotic manipulation or planning. From agriculture, the medical industry or to industrial manufacturing including the automotive industry. For car OEM's around the world, there have been significant increased uses in this advanced technology. EV manufacturing has reduced direct human interaction in the manufacturing assembly process by over 15%. This number will continously be reduced as the adaption to robotic manipulation/planning is introduced to more areas of the build and assembly process of cars.
Automotive Body In White Respot has always been the high volume visible application, sparks flying, robots busily moving from spot weld to spot weld. Geo spot weld is slower and harder to understand, with clamps and locators. One of the most challenging applications is Tandem Press cold stamping of large auto body panels, with heavy bulky payloads fighting the "wind resistance" and narrowly getting out of the press before the upper die closes. Painting BIW is like watching a ballet, waving back and forth as atomized colored paint transforms the black primed BIW into the beautiful sculpture the stylist imagined.
Robotic manipulation and motion planning still face challenges and opportunities for further improvement and innovation. These include dealing with the uncertainty and variability of the real world, such as noise, disturbances, or changes in the environment or task. Additionally, robots need to achieve higher levels of dexterity and complexity, such as manipulating soft or deformable objects or performing fine or delicate motions. They also need to collaborate and coordinate with other robots or humans, such as sharing information, resources, or goals, or adjusting their behavior or roles. Finally, robots need to learn and adapt to new situations, such as acquiring new skills, knowledge, or preferences, or improving their performance or efficiency.
Multi robotic path planning is maturing and becoming much more helpful, handheld tracker programming of free moves looks promising, optimizing loads to improve robot life could become quite popular, scaled up robot production and robot cost reduction could further drive robotic applications.