Robohub.org
 

Seegrid adds vision-guided lifting and stacking to product line


by
19 January 2014



share this:

Seegrid-walkie-stacker_400_237_80
Seegrid Corporation, a Pittsburgh-based start-up, has been providing driverless tugs for moving materials from point a to point b. Up until now they have just delivered the skids of material and then a human-operated forklift would lift the skids and place them on the racks

(or the reverse: a human-driven forklift would take from the racks and stack and place the materials so that they could be transported autonomously by a Seegrid tug to where the material was needed).

Now Seegrid is introducing an $80,000 driverless walkie stacker using an off-the-shelf* Class III forklift chassis equipped with Seegrid’s vision-guided autonomous navigation system so that the new device can provide the additional functions to transport: pick, stack and put away*. The tablet-driven walkie stacker GWSL3 is equipped with Seegrid’s vision-guided autonomous navigation system and will be launched at MODEX 2014 in Atlanta this coming March 17-20.

John Hayes, Seegrid VP of Sales and Marketing, said, “With the flexible GWS35 walkie stacker, we have expanded our traditional horizontal transportation line by adding a vehicle that allows for nearly all traditional AGV applications to be both simple and affordable.”

The new walkie stacker will work in conjunction with Seegrid’s new $75,000 vision-guided GT4 tugger. Both the walkie stacker and the tugger can also be leased instead of purchased.

__________________

* There have been rumors that Seegrid has chosen to focus on what it does best: provide vision, scanning and navigation systems and purchase off-the-shelf tugs and forklifts and outfit them with their special equipment and software. It is not known whether the new GWSL3 and GT4 are fully built by Seegrid or not.



tags:


Frank Tobe is the owner and publisher of The Robot Report, and is also a panel member for Robohub's Robotics by Invitation series.
Frank Tobe is the owner and publisher of The Robot Report, and is also a panel member for Robohub's Robotics by Invitation series.

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Robot Talk Episode 170 – Robots in the real world, with Daniela Shchegelskaya

  13 Nov 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Daniela Shchegelskaya from the University of Twente about getting robots to operate reliably in safety-critical environments.

AI100 report released: embodied AI highlighted as grand challenge

  11 Nov 2026
Embodied AI is listed as one of the most inspiring open grand challenges.

AIhub coffee corner: Are humanoids the future of embodied AI?

  09 Nov 2026
The AIhub coffee corner captures the musings of AI experts over a short conversation.

Robot Talk Episode 169 – Robot sensing inspired by nature, with Dexter Shepherd

  06 Nov 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Dexter Shepherd from the University of Sussex about using artificial intelligence to help robots understand and adapt to their environment.

Robots in society, business and culture: October 2026

We showcase a selection of robotics stories from society, business, research and culture.

Muscle coordination can be mimicked by electric motors – it could lead to improved robots

  02 Nov 2026
Researchers built a physical model using ordinary electric motors to try and simulate how muscles may perform tasks.

Robot Talk Episode 168 – Advancing robotics with novel electronics, with Zlatka Stoeva

  30 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Zlatka Stoeva from DZP Technologies about flexible, stretchable and soft printed electronics for dexterous robots.

Competing in RoboCup@Home and winning the 2026 best paper award: an interview with Raphael Memmesheimer

and   28 Oct 2026
Hear more about Raphael's research and his involvement in the RoboCup@Home league.


↑


AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence