Learnings from working + 20 years in robotics as an entrepreneur, teacher, lecturer, and researcher w/Lars Dalgaard

02/07/20 • 38 min

Lars Dalgaard shares his experiences developing robots in many different contexts.

We hear about Lars’ early work with large mobile robotics in a commercial nursery garden handling the transfer of plants from the greenhouse to the field.

He also speaks about the Hydra project a self re-configuring modular robotics project that developed several different modular robotics systems including the Atron system.

Lars felt that there was a problem with the process used to introduce robotics and automation into society. Commercialization was hard and unreliable mostly because there was no focus on designing a complete system. This lead to an industrial PhD done at the Danish Technological Institute (DTI) focusing on a system level design approach.

He then talks about his work at DTI that focuses on transferring research, knowledge and research results from academia into companies and the Danish society in general.

One project Lars has been working on is augmenting mobile platforms so that they can handle tasks as they move around in a production facility. This also aims to make it easier to program the mobile platforms and any systems added to them.

Lars thinks that looking at the bigger picture and bringing multiple partners and end users into projects, and doing so early, can bring big benefits to a project.

This podcast is part of the Wevolver network. Wevolver is a platform & community providing engineers informative content to help them innovate.
Learn more at Wevolver.com

Lars Dalgaard shares his experiences developing robots in many different contexts.

We hear about Lars’ early work with large mobile robotics in a commercial nursery garden handling the transfer of plants from the greenhouse to the field.

He also speaks about the Hydra project a self re-configuring modular robotics project that developed several different modular robotics systems including the Atron system.

He then talks about his work at DTI that focuses on transferring research, knowledge and research results from academia into companies and the Danish society in general.

Lars thinks that looking at the bigger picture and bringing multiple partners and end users into projects, and doing so early, can bring big benefits to a project.

This podcast is part of the Wevolver network. Wevolver is a platform & community providing engineers informative content to help them innovate.
Learn more at Wevolver.com

Previous Episode

Mimicking human decision making with algorithms w/Adjunct Professor Harri Ketamo

Harri talks about AI and how he aims to mimic human decision making with algorithms.

Harri has done a lot of AI for computer games to create opponents that are entertaining to play against. It is easy to develop a very bad or a very good opponent, but designing an opponent that behaves like a human, is entertaining to play against and that you can beat is quite hard. He talks about how AI in computer games is a very important story telling tool and an important part of making a game entertaining to play.

This work led him into other parts of the AI field. Harri thinks that we sometimes have a problem separating what is real from what is the type of story telling he knows from gaming AI. He calls for critical analysis of AI and says that data has to be used to verify AI decisions and results.

We also hear about the current use of AI in among other things sports games, where the challenge is to make a believable computer copy of a real-world player to make the games feel more real.

We then get to hear about his current work in developing AI systems that create mind-maps from texts to make the computer able to determine the context. By doing this we can derive better sentiment and meaning. This AI system is trained using a large amount of reliable data from scientific papers and CNN.

One application of this that Harri is working on, is in the labor market matching needs for talent with available people. This will help companies find staff and people find job opportunities.

This podcast is part of the Wevolver network. Wevolver is a platform & community providing engineers informative content to help them innovate.
Learn more at Wevolver.com

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Next Episode

The social robot revolution w/Gabriel Skantze

Gabriel Skantze talks about how he works with human robot communication, and about how the social robot revolution makes it necessary to communicate with humans in a human ways through speech and facial expressions. This is necessary as we expand the number of people that interact with robots as well as the types of interaction.

Gabriel gives us more insight into the many challenges of implementing spoken communication for co-bots, where robots and humans work closely together. They need to communicate about the world, the objects in it and how to handle them.

We also get to hear how having an embodied system using the Furhat robot head helps the interaction between humans and the system.
Having an expressive face like the Furhat adds many improvements to how a system can communicate with people. It also improves the human engagement and understanding of what the system tries to communicate significantly.

Gabriel then talks about the how they use AI and machine learning to understand speech. Understanding an individual speaker’s way to speak, thus adapting a robot to its user can improve their communication.

As the Furhat system is used out in the field, we get valuable insights from real world situations. One such case is guiding travellers at an airport to improve their experience and make travelling more efficient for everyone.

This podcast is part of the Wevolver network. Wevolver is a platform & community providing engineers informative content to help them innovate.
Learn more at Wevolver.com