Robohub.org
 

Precise Automation’s PF400 collaborative SCARA robot


by
26 August 2014



share this:

Precise Automation's PF400 collaborative SCARA robotSix months ago, after the publication of our revelatory feature article regarding the safety of Universal Robots’ UR5 collaborative robot arm, Precise Automation expressed their interest to have their one-of-a-kind PF400 collaborative SCARA robot undergo a similar study in our lab. The company claims that the PF400 is “intrinsically safe since all of the forces generated by its axes are limited so that the robot cannot hurt a user even if it collides with them at full speed.” I asked one of our undergraduate students to test the demo unit that we received on loan. So does he think we should leave the PF400 fenceless?


Precise Automation is a small company based in California, It was founded in 2004 by Mr. Brian Carlisle and Dr. Bruce Shimano, who were the founders of Adept Technology and key members of the team that developed the PUMA robot for Unimation. Precise Automation develops motion controllers, vision systems, Cartesian robots and SCARA robots. Their PreciseFlex SCARA robot was introduced several years ago as a “4-axis sample handler, with servo gripper, that is ideal for benchtop applications where price, ease-of-use, space requirements and safety are critical.”

The PF400 was released last year, but the PreciseFelx SCARA has been collaborative since it was released four years ago for the Life Science market. It uses servo motors equipped with absolute encoders and moves very quietly. Its controller is embedded inside the robot arm, which results in a very small footprint. The PF400 does not come with a physical teach pendant. The robot can be controlled using a web interface or it can run stand-alone in automatic mode. Teaching robot positions by demonstration is easy. Motors on axes 2, 3 and 4 can be deactivated (they don’t have brakes), while the break on axis 1 can be released by pushing a button beneath the proximal link of the robot. The robot can be programmed by using so-called motion blocks or with the help of a custom programming language.

PF400’s payload is only 0.5 kg and its linear speed is limited to 500 mm/s. In manual mode, the linear speed is further limited to 250 mm/s. Nevertheless, we performed a series of impact tests using our AMTI six-axis force plate. The maximum impact force registered during vertical motion (axis 1 only) was about 420 N. The maximum force in a horizontal motion was only 360 N. Furthermore, at large impacts, the robot is deactivated almost immediately (after 0.02 s) and the residual forces are very small (about 50 N in the case of vertical impact). Note, however, that our tests do not necessarily represent reality. Although we placed a small rubber mat on the robot at the impact location, this mat does not have exactly the same compliance as the different parts of the human body. A larger compliance will obviously lead to smaller impact forces and vice versa.

 

 

An interesting safety feature of the PF400 is that it can change from lefty to righty configuration, only by retracting its links, rather than by fully expanding them. This, however, might lead to slightly longer cycle times in some situations (compared to having no mechanical limit at the elbow joint). Furthermore, there is a risk of self-colision that cannot be prevented by the robot controller. This should be done in future versions. Finally, there is a risk of pinching between the distal link and the proximal link, but although we did not evaluate this risk properly, a serious injury seems highly improbable. Indeed, the company showed me a video of Brian Carlisle pinching his fingers intentionally.

Another potential safety risk is associated with the fact that the PF400 does not come with an emergency stop. Fortunately, such an E-stop can be easily connected to the robot’s base.

In conclusion, the most dangerous part of the robot is its gripper, due to its pointy shape. It is quite obvious that safety goggles must be worn by all personnel in the vicinity of the robot, when the latter is active. Other than that, the robot could hardly be any safer.

 




Ilian Bonev Ilian Bonev is professor at École de technologie supérieure (ÉTS) and holder of the Canada Research Chair in Precision Robotics.
Ilian Bonev Ilian Bonev is professor at École de technologie supérieure (ÉTS) and holder of the Canada Research Chair in Precision Robotics.





Related posts :



Robot Talk Episode 120 – Evolving robots to explore other planets, with Emma Hart

  09 May 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Emma Hart from Edinburgh Napier University about algorithms that 'evolve' better robot designs and control systems.

Robot Talk Episode 119 – Robotics for small manufacturers, with Will Kinghorn

  02 May 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Will Kinghorn from Made Smarter about how to increase adoption of new tech by small manufacturers.

Multi-agent path finding in continuous environments

  01 May 2025
How can a group of agents minimise their journey length whilst avoiding collisions?

Interview with Yuki Mitsufuji: Improving AI image generation

  29 Apr 2025
Find out about two pieces of research tackling different aspects of image generation.

Robot Talk Episode 118 – Soft robotics and electronic skin, with Miranda Lowther

  25 Apr 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Miranda Lowther from the University of Bristol about soft, sensitive electronic skin for prosthetic limbs.

Interview with Amina Mević: Machine learning applied to semiconductor manufacturing

  17 Apr 2025
Find out how Amina is using machine learning to develop an explainable multi-output virtual metrology system.

Robot Talk Episode 117 – Robots in orbit, with Jeremy Hadall

  11 Apr 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Jeremy Hadall from the Satellite Applications Catapult about robotic systems for in-orbit servicing, assembly, and manufacturing.

Robot Talk Episode 116 – Evolved behaviour for robot teams, with Tanja Kaiser

  04 Apr 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Tanja Katharina Kaiser from the University of Technology Nuremberg about how applying evolutionary principles can help robot teams make better decisions.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


©2025.05 - Association for the Understanding of Artificial Intelligence


 












©2025.05 - Association for the Understanding of Artificial Intelligence