Situational awareness in robot dogs

Thema:
Artifical intelligence

Some industrial environments are too complex and too dangerous for human inspectors. But not for robots. Disaster zones are a case in point, which is why TNO is developing a robot dog that helps people prevent disasters. But what if a disaster occurs anyway? In that case, the robot can carry out rescue operations autonomously.

Imagine the scene – a huge production site with large tanks containing chemical substances that are not only toxic, but also highly flammable. A leak or too-high pressure could have catastrophic consequences. Continual and meticulous inspections are therefore essential. These are currently carried out by people, but the work itself is very hazardous as there is always a risk of toxic gases escaping or of an explosion taking place.

Robot with artificial intelligence

Imagine the scene – a huge production site with large tanks containing chemical substances that are not only toxic, but also highly flammable. A leak or too-high pressure could have catastrophic consequences. Continual and meticulous inspections are therefore essential. These are currently carried out by people, but the work itself is very hazardous as there is always a risk of toxic gases escaping or of an explosion taking place.

SPOT the robot dog used for inspection and rescue work
SPOT the robot dog can be used for inspection work in dangerous situations instead of people.

Helping and saving people

But that’s not all. TNO is presently investigating what is needed for deploying the robot dog during rescue operations. In such situations, it will not only be helping people, but actually saving their lives. We are currently developing this intelligence.

Situational awareness during a disaster

For both inspection work and rescue missions alike, it is important that the robot is operational as soon as it is activated. It will have to be able to do its work immediately, autonomously, and intelligently. We refer to this as ‘turnkey intellect’. To actually get a robot to this level, it first has to pass through the following three stages:

  1. Making plans based on common sense. The robot has to know what situation it is in – that is, it must have situational awareness.
    At the same time, it has to be able to make hypotheses, such as whether there is a possible gas leak. It then has to verify its hypotheses according to what it observes in the real world. This means the robot must possess the knowledge that people have so far acquired in relation to hazardous situations. It should also be capable of learning new experiences itself.
  2. Anticipating. In any critical situation, there are so many factors at play that things can evolve at a rapid pace. In such cases, the robot will have to check whether its current plan is still feasible. If it is not, then it must quickly devise a new plan and act accordingly.
  3. Improvising. What happens if the camera fails during a measuring operation? There would be little point in the robot continuing to work on the basis of visual input. It would have to find other ways of carrying out its work, with the help of sounds or smells, for example.

Monitoring the robots remotely

Once the robot dogs actually start carrying out inspections and rescue operations, people will be able to monitor them remotely. That’s because they will constantly be sending information about their progress. In doing so, the robots will also be stating how far their knowledge and skills are relevant to the situation in which they find themselves.

Robot Dog Spot with State Secretary for Kingdom Relations and Digitalisation, Alexandra van Huffelen.
SPOT the robot dog interacts with State Secretary for Kingdom Relations and Digitalisation, Alexandra van Huffelen.

Get inspired

10 resultaten, getoond 1 t/m 5

Educating AI

Informatietype:
Insight
27 September 2022

You can read about how AI is educated in Chapter 1. How can we make clear to AI which goals we want to pursue as humans? Andhow can we ensure intelligent systems will always function in service of society?

Innovation with AI

Informatietype:
Insight
27 September 2022

What does that world look like in concrete terms? Using numerous examples, TNO has created a prognosis for the future in Chapter 2. Regarding construction, for example, in which AI will be used to check the quality, safety, and energy efficiency of buildings before they are actually built. Or healthcare, where robots will partly take over caregivers’ tasks and AI will be able to autonomously develop medicines.

Innovating with innovation AI

Informatietype:
Insight
27 September 2022

How AI will change research itself is explained in Chapter 3. For example, what role will AI be permitted to play in knowledge sharing? And what will happen when we make machines work with insurmountably large data sets?

David Deutsch on the development and application of AI

Informatietype:
Insight
27 September 2022

Peter Werkhoven, chief scientific officer at TNO, joins physicist, Oxford professor, and pioneer in the field of quantum computing, David Deutsch, for a virtual discussion. Deutsch set out his vision in 1997 in the book, The Fabric of Reality. Together, they talk about the significance of quantum computing for the development and application of AI. Will AI ever be able to generate ‘explained knowledge’ or learn about ethics from humans?

Georgette Fijneman on the promise of AI for health insurers

Informatietype:
Insight
27 September 2022

Hanneke Molema, senior consultant healthy living at TNO, interviews Georgette Fijneman, CEO of health insurer Zilveren Kruis since 2017. Both look at the same topic, health, from a completely different perspective. What is the promise of AI for one of the Netherlands’ largest health insurers?