Researchers from Brown University are developing a new algorithm to help robots better plan their actions in complex environments. It’s designed to help robots be more useful in the real world, but it’s being developed with the help of a virtual world — that of the video game Minecraft.
Basic action planning, while easy for humans, is a frontier of robotics. Part of the problem is that robots don’t intuitively ignore objects and actions that are irrelevant to the task at hand. For example, if someone asked you to empty the trashcan in the kitchen, you would know there’s no need to turn on the oven or open the refrigerator. You’d go right to the trashcan.
Robots, however, lack that intuition. Most approaches to planning consider the entire set of possible objects and actions before deciding which course to pursue. In other words, a robot might actually consider turning on the oven as part of its planning process for taking out the trash. In complex environments, this leads to what computer scientists refer to as the “state-space explosion” — an array of choices so large that it boggles the robot mind.
“It’s a really tough problem,” said Stefanie Tellex, assistant professor of computer science at Brown. “We want robots that have capabilities to do all kinds of different things, but then the space of possible actions becomes enormous. We don’t want to limit the robot’s capabilities, so we have to find ways to shrink the search space.”
The algorithm that Tellex and her students are developing does just that. David Abel, a graduate student in Tellex’s lab, led the work and will present it this week at the International Conference on Automated Planning and Scheduling.
Discovering the likely path
The algorithm augments standard robot planning algorithms using “goal-based action priors” — sets of objects and actions in a given space that are most likely to help an agent achieve a given goal. The priors for a given task can be supplied by an expert operator, but they can also be learned by the algorithm itself through trial and error.
The game Minecraft, as it turns out, provided an ideal world to test how well the algorithm learned action priors and implemented them in the planning process. For the uninitiated, Minecraft is an open-ended game, where players gather resources and build all manner of structures by destroying or stacking 3-D blocks in a virtual world. At over 100 million registered users, it’s among the most popular video games of all time.
“Minecraft is a really good a model of a lot of these robot problems,” Tellex said. “There’s a huge space of possible actions somebody playing this game can do, and it’s really cheap and easy to collect a ton of training data. It’s much harder to do that in the real world.”
Tellex and her colleagues started by constructing small domains, each just a few blocks square, in a model of Minecraft that the researchers developed. Then they plunked a character into the domain and gave it a task to solve — perhaps mining some buried gold or building a bridge to cross a chasm. The agent, powered by the algorithm, then had to try different options in order to learn the task’s goal-based priors — the best actions to get the job done.
“It’s able to learn that if you’re standing next to a trench and you’re trying to walk across, you can place blocks in the trench. Otherwise don’t place blocks,” Tellex said. “If you’re trying to mine some gold under some blocks, destroy the blocks. Otherwise don’t destroy blocks.”
After the algorithm ran through a number of trials of a given task to learn the appropriate priors, the researchers moved to a new domain that it had never seen before to see if it could apply what it learned. Indeed, the researchers showed that, armed with priors, their Minecraft agents could solve problems in unfamiliar domains much faster than agents powered by standard planning algorithms.
Having honed the algorithm in virtual worlds, the researchers then tried it out in a real robot. They used the algorithm to have a robot help a person in the task of baking brownies. The algorithm was supplied with several action priors for the task. For example, one action prior let the robot know that eggs often need to be beaten with a whisk. So when a carton of eggs appears in the robot’s workspace, it is able to anticipate the cook’s need for a whisk and hand him one.
In light of the results, Tellex says she sees goal-based action priors as a viable strategy to help robots cope with the complexities of unstructured environments — something that will be important as robots continue to move out of controlled settings and into our homes.
The work also shows the potential of virtual spaces like Minecraft in developing solutions for real-world robots and other artificial agents. “I think it’s going to provide a way for very rapid iteration for algorithms that we can then run in our robots and have some confidence they’re going to work,” Tellex said.
Read more: Using Minecraft to unboggle the robot mind
The Latest on: Robot planning algorithms
[google_news title=”” keyword=”Robot planning algorithms” num_posts=”10″ blurb_length=”0″ show_thumb=”left”]
via Google News
The Latest on: Robot planning algorithms
- Regina researchers reviewing robot potential in service industryon March 21, 2023 at 1:51 pm
A small team of researchers at the University of Regina is exploring how mobile robots can be used to address a labour shortage in the service industry. Dr. Yili (Kelly) Tang is leading the research ...
- The Humane Response to the Robots Taking Over Our Worldon March 21, 2023 at 4:36 am
“The promise of robots, AI, and advanced tech is to bring us (‘the humans’) closer to simplicity, intelligence, and abundance in our daily lives,” he says. “Yet much of the data used to train machine ...
- The 8 best robot lawn mowers of 2023, according to an experton March 20, 2023 at 7:00 pm
Enter the world of robot lawn mowers. Yes, it’s the buzzy, hands-free version of your traditional lawn mowers, but with a twist. They don’t take up much space in your shed, have a motor all on its own ...
- The robot will see you now: Why experts say AI in health care is not to fearon March 20, 2023 at 6:02 am
"We fear change," Garth says. He then looks down at the mechanical hand and begins to repeatedly smash it with a hammer. Many Americans have a similar reaction to change and technology, especially ...
- AI isn’t yet going to take your job — but you may have to work with iton March 20, 2023 at 5:22 am
Artificial intelligence is increasingly making its way across industries, changing jobs from retail to medicine to marketing.
- Robot Controllers Market Outlook and Forecast till 2028on March 19, 2023 at 11:33 pm
The "Robot Controllers Market" study describes how the technology industry is evolving and how major and emerging ...
- Drawing Robot Creates Portraits Using Pen, Paper And Algorithmson March 17, 2023 at 5:00 pm
If you like what you see, the robot will then begin to draw your portrait ... which runs a rather sophisticated algorithm to generate a vector image which doesn’t take too long to draw, but ...
- Rise of the racist robots – how AI is learning all our worst impulseson March 15, 2023 at 7:19 am
Does a horrifying future await people forced to live at the mercy of algorithms? In May last year, a stunning report claimed that a computer program used by a US court for risk assessment was ...
- All rise for the robot judge: AI and blockchain could transform the courtroomon March 13, 2023 at 6:00 am
Joshua Browder, CEO of AI startup DoNotPay, attempted to bring a robot lawyer into a California courtroom, despite almost certainly knowing that it was illegal in almost all 50 states to bring ...
- Rescue Robot Market Size 2023 - 2030 Sales, Revenue, Trends, Current Development, Demand Supply Situation.on March 10, 2023 at 1:38 pm
A thorough analysis of a particular market and its submarkets is provided by the market research report on Rescue Robot. Knowing which facets of the Rescue Robot market will be examined is crucial for ...
via Bing News