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Bench Talk for Design Engineers

Bench Talk


Bench Talk for Design Engineers | The Official Blog of Mouser Electronics

Lost in Space Robot Evolves in Motion John Blyler

Lost in Space Robot Evolves in Motion | Empowering Innovation Together 2018In recent years, the high-tech industry has made great strides in advancing robotic motion technologies. Today’s robots can roll around on wheels or even walk upright, mimicking bipedal humans by climbing stairs and getting up after they fall down. Such accomplishments require a keen sense of balance and awareness of both position and motion. These functions also happen to be key elements in collaborative robots that can work side by side with humans in a safe and useful manner.

While still an emerging reality in the real world, science fiction has long been populated with mobile, collaborative robots. Remember the half-century-old TV series, Lost in Space? It had the B9 Robot—usually just called “Robot”—that roamed the universe with the Robinson family. Even the 1998 feature film remake had an evolved version of Robot, as will Netflix’s upcoming 2018 reboot of the TV series.

How hard has it been to turn the science fiction of mobile robots into reality? Let’s use the evolution of Robot as our guide to highlight the advances in robotic mobility technologies, specifically those needed for balance, motion, and location awareness.

The Mission

The original 1965 TV series has been described as a retelling of Johann David Wyss’s 1812 The Swiss Family Robinson. The clipper ship of the 19th century was replaced with a spaceship (the Jupiter) and modernistic technology. Instead of being marooned on an island, the TV series Robinson family was marooned on an unknown planet while trying to reach the solar system surrounding Earth’s nearest star, Alpha Centauri.

Each subsequent remake of Lost in Space follows the same basic story of the adventures of a colonizing family whose spaceship veers off course and becomes lost. In each retelling, Robot plays a major role both hindering and assisting the family. The only difference appears in the 2018 Netflix version, in which Robot first appears on the mysterious planet where the Robinson’s spacecraft initially crashes, and it operates as a highly advanced in robotic form with artificial intelligence (AI). He walks upright on two legs, like a humanoid, while in past incarnations, Robot moved on motorized, tank-like treads.

Using its AI, the robot seems to be on a mission to learn about the world around it before it meets the Robinsons. For example, during its first encounter with Will Robinson, the youngest family member, the robot learns to be gentle when tossing a rock. The capability to adjust for the safety of humans clearly shows the collaborative nature of its design.

Balance and Motion

Humans often forget their earliest years when maintaining balance, walking on two legs, and navigating to where they wanted to go was still something to be learned. None of these tasks are any easier for robots as the slow progress in modern technology has shown (Figure 1).

Figure 1: Newborn humans and robots struggle with the challenging tasks of balance and motion.

Figure 1: Newborn humans and robots struggle with the challenging tasks of balance and motion.

Of course, Robot versions in the TV series were actually men in robot costumes. But had they been actual robots, each would have needed a way to balance themselves while standing, lifting a load, and during motion. To achieve these tasks, each would have also needed an inertial navigation system (INS) with motion sensors (or accelerometers) and rotation sensors (or gyroscopes) that provided data to a computer to calculate their position, orientation, and velocity. (Note: Interestingly, the movie version did use a radio control unit to move Robot, which indeed was a robot.)

Unlike todays earthbound robots, those in the Lost in Space story couldn’t rely on a Global Positioning System (GPS) of satellites to tell them their position on the planet. Instead, they required their own self-contained internal systems to move around on the planet.

Balancing a motionless robot is one thing. Balancing a robot in motion or carrying a load is more difficult. In either case, gyros can be used to determine orientation, that is, to measure a rotation from a balanced position that can determine adjustments to maintain uprightness.

Judging from all the whirling gyroscopes in the original Lost in Space Robot, balance was achieved with old-school analog, mechanically spinning tops (Figure 2). In later versions of Robot, the spinning, mechanical gyros were probably replaced with new technology to determine angular rate, such as ring laser gyros or tiny microelectromechanical system (MEMS)-based gyros that use vibrating structures of small, resonating, mass sensors to detect shifts in angular velocity.

Figure 2: This is the original “Robot” from Lost in Space.

Figure 2: This is the original “Robot” from Lost in Space. (Source: Joamm Tall/CC BY-SA 2.0) 

An example of an angular rate sensor (or “gyroscope”) is the ADXRS450 from Analog Devices. This tiny chip would be a good choice for a robot that must travel over rugged terrain, as the chip uses a differential quad sensor to reject the influence of linear acceleration in harsh environments where shock or vibration are present.

Let’s consider the measurement of linear motion. A modern INS would contain an array of complementary inertial sensors to measure motion in as many ways as possible (e.g., accelerometers, gyros, magnetometers) (Figure 3).

Figure 3: This is an accelerometer and gyroscope sensor chip on a tiny board for wearables or robots.

Figure 3: This is an accelerometer and gyroscope sensor chip on a tiny board for wearables or robots.

Magnetometers are devices that measure the relative change of a magnetic field at a particular location. When used to measure the direction of an ambient magnetic field, the magnetometer becomes a compass. This would be an invaluable inertial navigation aid for a robot stranded on an unknown planet.

Inertial Measurement Units (IMUs) typically provide six degrees of freedom, meaning that they contain three accelerometers—one for each of the three physical coordinates (x, y, and z)—plus three gyroscopes for each axis. In IMUs, the number of degrees of freedom are the number of independent readings that are available. Some of the latest IMUs have nine degrees of freedom, adding three magnetometers to the existing inertial-sensor mix.

Taking it one degree further, the Analog Devices ADIS-16488 inertial sensor chip boasts ten degrees of freedom, where the tenth degree is in the realm of pressure measurements. Pressure differences would indicate elevation changes in a terrain, which would be very useful data for an inertial measurement system. A single-chip package like this one would probably have been used in the 1998 feature film or in the upcoming 2018 Netflix TV series.

From spinning mechanical gyros to ten-degrees-of-freedom inertial sensors on a tiny chip, the technologies used in the Robinson’s Robot has changed, particularly as the shape and mobility of this robot has evolved from the original tank treads to contemporary humanoid legs. One can only wonder what the next incarnation of “Robot” will look like or how it will move. Perhaps it will just float above the ground as it forever wanders on distant planets while lost in space.

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John Blyler is a technology professional with expertise in multi-discipline Systems Engineering, technical program life-cycle management (PLM), content development, and customer-facing projects. He is an experienced physicist, engineer, manager, journalist, textbook author, and professor who continues to speak at major conferences and before the camera. John has many years of experience leading interdisciplinary (mechanical-electronic, hardware-software) engineering teams in both the commercial and Mil/Aero semiconductor and electronics industries. Additionally, he has served as an editor-in-chief for technical trade journals and the IEEE professional engineering society publications. He was the founding advisor and affiliate professor for Portland State University’s online graduate program in systems engineering. Finally, John has co-authored several books on systems engineering, RF wireless design, and automotive hardware-software integration for Wiley, Elsevier, IEEE, and SAE.

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