The Stanford Cart in 1979, testing its ability to avoid objects. (Image credit: The Board of Trustees of the Leland Stanford Junior University)

When the Stanford Cart was first built, the control signals between the remote operator and the cart could imitate the 2.6-second delay that occurred in radio communications between the Earth and the Moon. Given the challenges of steering the cart with such a delay, the researchers added a predictive system that showed the operators where the cart would be when it started to act on the next command. Despite this, the experiments made clear that a lunar vehicle would need to move extremely slowly to be steered reliably.

About a decade after it was built, the cart was reborn as an autonomous vehicle. Brought outside, it rolled along at a consistent walking pace, following a white line. This tracking worked sometimes but inconsistencies in lighting, visual interference from other objects or an abrupt curve could all throw the cart off its course.

In its final form, the cart was equipped with 3D vision capabilities. It was also reconfigured to pause after each meter of movement and take 10-15 minutes to reassess its surroundings and reevaluate its decided path. In 1979, this cautious version of the cart successfully made its way 20 meters through a chair-strewn room in five hours without human intervention.

In 1987, the Stanford Cart was included in the Robot Theater at the Digital Computer Museum in Boston, alongside Shakey and the Stanford Arm. It is now on display at the Computer History Museum in Mountain View, California.

Go to the web site to view the video.

EXTRA: On his personal website, Lester Earnest, who was executive officer at SAIL while the cart was in development, recalls posting the custom “CAUTION ROBOT VEHICLE” sign. He said it became a surprisingly costly item because it was stolen so often.

The Stanford Cart in 1979, testing its ability to avoid objects. (Image credit: The Board of Trustees of the Leland Stanford Junior University)

When the Stanford Cart was first built, the control signals between the remote operator and the cart could imitate the 2.6-second delay that occurred in radio communications between the Earth and the Moon. Given the challenges of steering the cart with such a delay, the researchers added a predictive system that showed the operators where the cart would be when it started to act on the next command. Despite this, the experiments made clear that a lunar vehicle would need to move extremely slowly to be steered reliably.

About a decade after it was built, the cart was reborn as an autonomous vehicle. Brought outside, it rolled along at a consistent walking pace, following a white line. This tracking worked sometimes but inconsistencies in lighting, visual interference from other objects or an abrupt curve could all throw the cart off its course.

In its final form, the cart was equipped with 3D vision capabilities. It was also reconfigured to pause after each meter of movement and take 10-15 minutes to reassess its surroundings and reevaluate its decided path. In 1979, this cautious version of the cart successfully made its way 20 meters through a chair-strewn room in five hours without human intervention.

In 1987, the Stanford Cart was included in the Robot Theater at the Digital Computer Museum in Boston, alongside Shakey and the Stanford Arm. It is now on display at the Computer History Museum in Mountain View, California.

Go to the web site to view the video.

EXTRA: On his personal website, Lester Earnest, who was executive officer at SAIL while the cart was in development, recalls posting the custom “CAUTION ROBOT VEHICLE” sign. He said it became a surprisingly costly item because it was stolen so often.

Front view of Shakey the robot (Image credit: © Mark Richards. Courtesy of the Computer History Museum)

On its wheeled base, Shakey had cat whisker bump sensors and a push bar. Its center was a box of electronics that included a camera control unit and on-board computer. On top, the nearly 5-foot robot had a TV camera, an infrared triangulating range finder and an antenna for two-way radio communication.

Shakey’s operators sent it to carry out tasks via teleprinted instructions. Juddering through its “playroom,” the robot had to avoid running into walls and blocks, and navigate up ramps and through doorways. The robot had an incomplete map of its room and kept track of its position by counting wheel revolutions, which was fairly precise. When revolution-counting did not bring Shakey to its intended location or when the robot found itself somewhere unexpected, it used its TV camera and range finder to scan landmarks and objects – all of which were painted either red or black so Shakey’s camera could see them.

Go to the web site to view the video.

Given a task, such as “push the block off the platform,” Shakey could accomplish its goal without the step-by-step instructions required by other robots. It did this by building up a repertoire of simple actions – such as roll, turn and tilt or pan the camera – and strung those together to perform more complex tasks. Shakey also remembered multi-step plans it had executed in the past and could recall or adjust them for future tasks.

The Stanford Research Institute formally separated from Stanford University in 1970 and the Shakey project ended in 1972 when funders required more direct applications. In 1977, the Stanford Research Institute was renamed SRI International. Shakey can still be seen on display at the Computer History Museum in Mountain View, California.

EXTRA: Shakey was originally hardwired to receive and send information back to its operator. To avoid twisting these wires, the researchers programmed Shakey’s software to occasionally interrupt whatever else was going on so the robot could unwind. Even once the robot became wireless, it would still sometimes perform this now-functionless dance. In this video of an SRI International symposium on Shakey, computer scientist and Shakey developer Bertram Raphael likened it to Shakey recalling a “previous life.”

Front view of Shakey the robot (Image credit: © Mark Richards. Courtesy of the Computer History Museum)

On its wheeled base, Shakey had cat whisker bump sensors and a push bar. Its center was a box of electronics that included a camera control unit and on-board computer. On top, the nearly 5-foot robot had a TV camera, an infrared triangulating range finder and an antenna for two-way radio communication.

Shakey’s operators sent it to carry out tasks via teleprinted instructions. Juddering through its “playroom,” the robot had to avoid running into walls and blocks, and navigate up ramps and through doorways. The robot had an incomplete map of its room and kept track of its position by counting wheel revolutions, which was fairly precise. When revolution-counting did not bring Shakey to its intended location or when the robot found itself somewhere unexpected, it used its TV camera and range finder to scan landmarks and objects – all of which were painted either red or black so Shakey’s camera could see them.

Go to the web site to view the video.

Given a task, such as “push the block off the platform,” Shakey could accomplish its goal without the step-by-step instructions required by other robots. It did this by building up a repertoire of simple actions – such as roll, turn and tilt or pan the camera – and strung those together to perform more complex tasks. Shakey also remembered multi-step plans it had executed in the past and could recall or adjust them for future tasks.

The Stanford Research Institute formally separated from Stanford University in 1970 and the Shakey project ended in 1972 when funders required more direct applications. In 1977, the Stanford Research Institute was renamed SRI International. Shakey can still be seen on display at the Computer History Museum in Mountain View, California.

EXTRA: Shakey was originally hardwired to receive and send information back to its operator. To avoid twisting these wires, the researchers programmed Shakey’s software to occasionally interrupt whatever else was going on so the robot could unwind. Even once the robot became wireless, it would still sometimes perform this now-functionless dance. In this video of an SRI International symposium on Shakey, computer scientist and Shakey developer Bertram Raphael likened it to Shakey recalling a “previous life.”

Go to the web site to view the video.

STAIR’s first major achievement came in 2006 when researchers led by Andrew Ng, who was an assistant professor of computer science at the time, developed an algorithm that taught STAIR to identify five objects – a coffee cup, pencil, brick, book and martini glass – and the best way to pick each one up. With this knowledge, the robot could make its own decisions about how to handle unknown objects. For example, it decided to hold a roll of duct tape in a fashion that combined how it grasped a cup handle and a book.

Eighteen months into the project, the researchers also collaborated with the Personal Robotics Program, led by Kenneth Salisbury, a professor of Computer Science and of Surgery (now emeritus) to produce a personal robot prototype. It looked like a large torso with two fabric-covered arms, each of which could hold about ten pounds but also provide a gentle touch. At this point, the robot was remotely controlled but the researchers were working on a platform to help it, STAIR and other robots be capable of more independent operations.

Members of the STAIR project and the Personal Robotics Program pursued many tasks, including unloading a dishwasher, preparing simple meals and fetching an object from another room, prompted by voice command. Although those tasks were fun, the main mission of STAIR was to integrate aspects of artificial intelligence research that were often worked on in isolation, such as language processing, machine vision, machine learning and decision analysis.

The STAIR project ended in 2009 but its legacy lives on in the Robot Operating System developed by the team over the course of the project. ROS is an open-source framework for writing robot software used by robotics labs all over the world – and beyond. It ran on Robonaut 2 aboard the International Space Station in 2014.

Go to the web site to view the video.

STAIR’s first major achievement came in 2006 when researchers led by Andrew Ng, who was an assistant professor of computer science at the time, developed an algorithm that taught STAIR to identify five objects – a coffee cup, pencil, brick, book and martini glass – and the best way to pick each one up. With this knowledge, the robot could make its own decisions about how to handle unknown objects. For example, it decided to hold a roll of duct tape in a fashion that combined how it grasped a cup handle and a book.

Eighteen months into the project, the researchers also collaborated with the Personal Robotics Program, led by Kenneth Salisbury, a professor of Computer Science and of Surgery (now emeritus) to produce a personal robot prototype. It looked like a large torso with two fabric-covered arms, each of which could hold about ten pounds but also provide a gentle touch. At this point, the robot was remotely controlled but the researchers were working on a platform to help it, STAIR and other robots be capable of more independent operations.

Members of the STAIR project and the Personal Robotics Program pursued many tasks, including unloading a dishwasher, preparing simple meals and fetching an object from another room, prompted by voice command. Although those tasks were fun, the main mission of STAIR was to integrate aspects of artificial intelligence research that were often worked on in isolation, such as language processing, machine vision, machine learning and decision analysis.

The STAIR project ended in 2009 but its legacy lives on in the Robot Operating System developed by the team over the course of the project. ROS is an open-source framework for writing robot software used by robotics labs all over the world – and beyond. It ran on Robonaut 2 aboard the International Space Station in 2014.

Go to the web site to view the video.

A gecko’s toes are made of a series of microscopic flaps – which are themselves constructed of even smaller hair-like structures that are bundles of even smaller nanostructures. When in very close contact with a surface, those flaps create a molecular attraction called van der Waals forces.

With these forces in place, a gecko can support its whole body with one toe. The gecko-inspired adhesive is a simplified version of what geckos have but works the same way. It therefore does not require any squeezing and leaves no residue because it is not gooey or tacky.

Making the adhesive grip is as simple as pushing the flaps in the right direction. The Stickybot team activated the robot’s grip by adding a tail, which pulled the flaps into their “on” position.

Go to the web site to view the video.

The adhesive that brought a lab to new heights also picked up basketballs, wallets and burritos and helped tiny drones tug objects 40 times their weight. It even made its way to the International Space Station and a parabolic airplane flight – which simulates zero-G conditions. Now, the researchers are hoping the adhesive can venture outside the space station (to eventually help clean up space debris) and into consumer goods.

Go to the web site to view the video.

A gecko’s toes are made of a series of microscopic flaps – which are themselves constructed of even smaller hair-like structures that are bundles of even smaller nanostructures. When in very close contact with a surface, those flaps create a molecular attraction called van der Waals forces.

With these forces in place, a gecko can support its whole body with one toe. The gecko-inspired adhesive is a simplified version of what geckos have but works the same way. It therefore does not require any squeezing and leaves no residue because it is not gooey or tacky.

Making the adhesive grip is as simple as pushing the flaps in the right direction. The Stickybot team activated the robot’s grip by adding a tail, which pulled the flaps into their “on” position.

Go to the web site to view the video.

The adhesive that brought a lab to new heights also picked up basketballs, wallets and burritos and helped tiny drones tug objects 40 times their weight. It even made its way to the International Space Station and a parabolic airplane flight – which simulates zero-G conditions. Now, the researchers are hoping the adhesive can venture outside the space station (to eventually help clean up space debris) and into consumer goods.

Graduate students Joseph Greer, left, and Laura Blumenschein, right, work with Elliot Hawkes, a visiting assistant professor from the University of California, Santa Barbara, on a prototype of the Vinebot. (Image credit: L.A. Cicero)

Thanks to its squishy, air-filled form, Vinebot can squeeze through tight spaces, wrap around obstacles and grow up into the air. The lab that developed Vinebot has several versions. Some navigate somewhat spontaneously – when these encounter an obstacles, they simply grow around it – and others have predetermined shapes or pulley systems that direct them.

Go to the web site to view the video.

The researchers envision many roles for Vinebot. It could help with search and rescue operations, extending into the sky as a makeshift radio tower or growing through and propping up rubble. Topped with a camera, it could help locate buried people – and artifacts. Vinebot could make its way to a fire, fill with water and then burst upon arrival at the flame. The lab is also considering medical applications. Unlike a tube pushed through the body, this type of soft robot could grow without dragging along delicate structures.

Graduate students Joseph Greer, left, and Laura Blumenschein, right, work with Elliot Hawkes, a visiting assistant professor from the University of California, Santa Barbara, on a prototype of the Vinebot. (Image credit: L.A. Cicero)

Thanks to its squishy, air-filled form, Vinebot can squeeze through tight spaces, wrap around obstacles and grow up into the air. The lab that developed Vinebot has several versions. Some navigate somewhat spontaneously – when these encounter an obstacles, they simply grow around it – and others have predetermined shapes or pulley systems that direct them.

Go to the web site to view the video.

The researchers envision many roles for Vinebot. It could help with search and rescue operations, extending into the sky as a makeshift radio tower or growing through and propping up rubble. Topped with a camera, it could help locate buried people – and artifacts. Vinebot could make its way to a fire, fill with water and then burst upon arrival at the flame. The lab is also considering medical applications. Unlike a tube pushed through the body, this type of soft robot could grow without dragging along delicate structures.