When we navigate our way through busy environments, we place an awful lot of trust in our fellow human not to behave in a silly and unpredictable way. This allows us to perform incredibly complex navigational tasks without giving it a moments thought.
Such navigational abilities is not something that we can take for granted when we develop robots however. A recent paper by a team of Cornell researchers examined this prickly process in more detail.
“The key insight to the research is that we’re trying to minimize uncertainty when people are around a robot that’s moving,” the researchers say. “In a human pedestrian situation, we all implicitly trust each other to behave in a competent manner. If I move right in a hallway, you will mirror that behavior. Building this same trust in robots is non-trivial because trust comes with prediction. There will be a smooth, socially competent experience if I trust the robot will go by me.”
Gaining trust
After observing the way humans navigate through complex environments, the researchers spotted patterns similar to the topological concept of braids. The paths we take are akin to strings in space-time that weave together in complex patterns.
“This leads to a framework that can consider possible alternatives – patterns so a robot can conceive what the human may be thinking in terms of which way to go, analyze the possible intention and come up with a compatible navigational strategy,” the researchers say.
This will be crucial when the novelty of seeing robots on the streets wears off and we start interacting with them in the same way we do other people today.
“Overcoming mistrust is the goal,” the researchers say. “As robots become more aware, we’d like them to understand more deeply the ways in which humans react. If you understand the language of motion that people naturally speak, you can use that to a robot’s advantage. It all leads to a smoother interaction for humans and robots.”
We’ve already seen a number of delivery robots, such as those developed by Starship Technologies, hit the streets, so the paper provides a nice addition to the narrative around how these can successfully engage with humans.