Image: ESA/ATG medialab

In Darmstadt, Germany, European Space Agency (ESA) teams are scrambling to confirm contact with the Entry, Descent and Landing Demonstrator Module (EDM), Schiaparelli—the spectre of Philae still haunting the European Space Operations Centre (ESOC). Whether or not ESA ever speak to Schiaparelli again, the risky business of space robotics is once more laid bare.

Editors note: Since this article was written, ESA are attempting to decode a partial signal from the EDM

After Schiaparelli’s release from its mothership—The Trace Gas Orbiter (TGO)—the 577 kg EDM was programmed to autonomously perform an automated landing sequence, with parachute deployment and front heat shield release between 11 and 7 km above the Martian surface, all the time collecting data on the pressure, surface temperature and heat flux on its back cover as it passed through the atmosphere.  Then, 1100 m from the ground, retrorocket braking was supposed to slow the EDM before a final fall from a height of 2 m, protected by a crushable structure. But sometime during this process the signal was lost. ESA_Shiaparelli’s twitter feed soon fell silent also.

If Schiaparelli reached the surface safely, its batteries should be able to support operations for three to ten days, offering multiple opportunities to re-establish a communication link and collect data from its suite of sensors designed to measure wind speed and direction, humidity, pressure, atmospheric temperature, transparency of the atmosphere, and atmospheric electrification. But if contact is never restored, it’ll be a hefty blow to ExoMars and ESA’s aim of testing key technologies in preparation for their contribution to subsequent missions to Mars, including a planned 2020 rover that will carry a drill and a suite of instruments dedicated to exobiology and geochemistry research.

Image: ESA/ATG medialab

Such robotic technology has the potential to stretch our cosmological horizon, and perhaps even detect traces of extra-terrestrial life. But there’s a cost.  The ExoMars program runs up a bill totaling €1.3 billion, and such failures (if a failure it be) naturally raise questions of risk versus reward, particularly in tight economic times. Michael Johnson of the Pervasive Media Studio, Bristol, and founder of PocketSpacecraft.com, once told me during an interview: “About 50% of space missions fail after launch.” He shrugged. “That’s life… This is a high risk, high reward activity.”

In no other field of robotics is the potential of catastrophic failure so present and accepted. But how long can this attitude be maintained? The consensual public funding of—and indeed existence of—future space missions is parasitic upon the success of space robots and automated technology, and vice versa. Can you hear us Schiaparelli?

…

Come in, Schiaparelli.

…?

Image: ESA/ATG medialab

BUT ALL IS NOT LOST. The difficulties surrounding the mission’s EDM might potentially overshadow the successes of its TGO, which successfully performed the long 139-minute burn required to be captured by Mars, and has entered an elliptical orbit around the Red Planet. TGO’s Mars orbit Insertion burn lasted from 13:05 to 15:24 GMT on 19 October, reducing the spacecraft’s speed and direction by more than 1.5 km/s. The TGO is now on its planned orbit around Mars, primed with a suit of scientific equipment to measure the Martian atmosphere from on high. You win some, you lose some. This 50:50 success rate exemplifies the apparent nature of space robotics.

Click here to keep up to date with the latest ExoMars developments.

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What are you thinking? Robots and humans working together need to understand – and even trust – each other. NASA Johnson/flickr

If we are serious about long-term human presence in space, such as manned bases on the moon or Mars, we must figure out how to streamline human-robot interactions.

Right now, even the most basic of robots seem to have impenetrable brains. When I bought an autonomous vacuum cleaner, one that roams the house on its own, I thought I was going to save time and be able to enjoy a book or a movie, or play longer with the kids. I ended up robot-proofing every room, making sure wires and cables are out of the way, closing doors, placing electronic signposts for the robot to follow and much more – often daily. I cannot fully understand or predict what the system will do, so I don’t trust it. As a result, I play it safe, and spend time doing things to accommodate the needs I imagine the robot might have.

As a space roboticist, I think about this sort of problem happening in orbit. Imagine an astronaut on a spacewalk, working on repairing something damaged on the outside of the spacecraft. Several tools might be needed, and parts to mend or replace others. An autonomous spacecraft could serve as a floating toolbox, holding parts and tools until they’re needed, and staying close to the astronaut as she moves around the area needing to be fixed. Another robot could be clamping parts together before they are permanently fastened.

How will these robots know where they’ll be needed to go next, to be useful but not in the way? How will the astronaut know whether the robots are planning to move to the place she actually needs? What if something comes loose unexpectedly – can the person and the machinery figure out how to stay out of each other’s way while handling the situation efficiently? In weightless space, spatial orientation is difficult and the dynamics of moving around one another are not intuitive.

Problems around effective communication between people and their machines – particularly about actions and intentions – arise throughout the field of robotics. They must be solved if we are to fully take advantage of the potential robots enable for us.

Feeling safe crossing the road

Understanding robots is already an increasing problem here on Earth. One day I found myself walking down a California road where autonomous cars are tested. I asked myself, “How would I know if a driverless vehicle is going to stop at the crosswalk?” I have always relied on eye contact and cues from the driver, but those options may be soon gone.

Robots have trouble understanding us, too. I recently read of an autonomous car unable to process a situation where a bicycle rider balanced himself for some time at an intersection, without putting his feet down. The onboard algorithms could not determine if the biker was going or staying.

A self-portrait of the Mars rover Curiosity.
Source: NASA/JPL-Caltech/Malin Space Science Systems

When we look at space exploration and defense, we find similar problems. NASA has not used the full abilities of some of its Mars rovers, simply because the engineers could not be sure what would happen if the metallic pets were free to explore and investigate the Red Planet on their own. The humans didn’t trust the machines, so they prevented them from doing as much as they could.

The Department of Defense often uses crews of 10 or more trained personnel to support a single unmanned aerial vehicle up in the sky. Is such a drone really autonomous? Does it require the people, or do the people need it? In any case, how do they interact?

What is “autonomy,” really?

While “autonomy” means “self-governance” (from Greek), no man is an island; the same appears to be valid for our robotic creations. Today we see robots as agents able to operate independently – like my vacuum cleaner – but still part of a team – the family’s efforts to keep the house clean. If they are truly working with us, rather than instead of us, then communication is key, as well as the ability to infer intent. We may go solo for most duties, but sooner or later we will need to be able to connect with the rest of the team.

Do drones need people or do people need drones? Source: U.S. Air Force/Wikipedia Commons

The problem is that autonomous machines and humans do not fully understand each other, and often speak in languages each other does not know – and has not yet started to learn.

The question for the future is how we transmit intent between humans and robots, in both directions. How do we learn to understand – and then to trust – machines? How do they learn to trust us? What cues might each offer the other? Understanding intentions and trusting our fellow humans is already a bumpy ride, but at least we have known cues we can rely on – like pedestrian-driver eye contact at a crosswalk. We need to find new ways to read robots’ minds, the same way they need to be able to understand ours.

Perhaps an astronaut could be given a specialized display to show what the helper spacecraft’s intentions are, much like the gauges in an airplane cockpit show the plane’s status to the pilot. Maybe the displays would be embedded in a helmet visor, or enhanced by sounds that have specific meanings. But what information would they transmit, and how would they know it?

These questions are open ground for new work, the type of learning we’ll need to find to unlock an exciting future of unimaginable exploration in which a new species, the robot, can lead us farther than ever before.

This article was originally published on The Conversation. Read the original article.

At Keio University in Japan, the Ishigami Laboratory, in the Faculty of Science and Technology, Department of Mechanical Engineering, is investigating robotic mobility systems. The main mission of this group is to perform fundamental and applied research for application to extreme environments, notably lunar and planetary rovers.

“In our lab, we focus on field robotics that works for extreme environments.”

“For example, we investigate the interaction mechanics between robots and sandy surfaces, taking into account “off-the-road locomotion.”Also, because such robots would be deployed in unknown environments, we also work on vision systems such as cameras and laser rangefinders.”

In this research, there are three key concepts: vehicle-terrain interaction mechanics, autonomous mobility systems, and robotic device development.

In vehicle-terrain interaction mechanics, the researchers analyze vehicle behavior using a dynamic simulator. They’re also developing vehicle-slip compensation systems and in-wheel-sensor systems.

“In the study of interaction mechanics, we first focus on a wheel itself using a “single-wheel testbed.” We put just one wheel on the testbed, and perform experimental runs to obtain wheel force data under different sets of slip parameters. Meanwhile, we numerically calculate wheel force based on a wheel-sand interaction model we developed. Then, we compare the experimental results with the numerical ones, so we can evaluate how valid the interaction model is. Applying this approach to a whole robot-vehicle system, it is possible to simulate how the robot behaves dynamically in an unknown environment. That’s the key approach in this research.”

“Sand flow investigation has received especially close attention in recent years. In our lab, of course, we’ve recently taken such an approach, called particle image velocimetry, or PIV, which has been widely used in fluid mechanics. PIV enables us to clearly determine the sand flow, helping to develop a well-defined interaction model.”

In the area of autonomous mobility systems, the Ishigami Lab is working on environment recognition using laser rangefinders and camera images, as well as robotlocalization, path planning, teleoperation, and integrated sensory processing systems.

“For example, in an unknown environment, there aren’t any road signs, saying ‘there’s an obstacle here,’ or ‘turn right at the next intersection.’ Such obstacles should be detected by onboard cameras, or laser rangefinders which operate based on the time-of-flight principle (measuring the time from a laser emission to detection of the reflected laser.). In our research, we effectively utilize such devices to obtain 3D distance data or 3D environment information. Based on these data, the robot itself decides how to travel. Such systems are called autonomous mobility systems.”

“One typical point of our lab is, I would say, we’re focusing on mechanics as well as autonomous mobility, applying both hardware and software approaches.. In general, one lab has one specific point of interest for research, and looks more deeply into that, but in our lab, we work on mechanics and also on autonomous mobility systems, so we pursue several topics in parallel. Robots consist of integrated technology, so we consider them as total systems.
In addition, another feature of our research is, we consider that field tests are extremely important. We actually take our robots to outdoor environments such as volcanic regions on Izu Oshima and Mt. Aso, and operate them in rough terrain, to test how they act in actual environments.”

“The field of robotics comprises a variety of technologies. So, rather than sticking to a single academic discipline, we’d like students to do research from a broad perspective.”