Robots that use educated guesswork to build maps of their surroundings are being tested by US researchers. The approach could let them navigate more easily through complex environments such as unfamiliar buildings, the researchers claim.Navigation is one of the biggest challenges faced by mobile robots. One popular technique, dubbed SLAM (simultaneous localisation and mapping), involves having a robot build a map of the local area, whilst also tracking its position (see Uncharted territory).
While humans find it easy to create “mental maps” in this way, it is difficult and time consuming for a robot to perform the same task.
Robots typically use laser scanners and odometers to measure distances for mapping. To speed up this process, and to make it more accurate, researchers have previously tried using different algorithms, or set teams of robots to explore an area together.
Now, George Lee and colleagues at Purdue University, US, have come up with an altogether different approach. They have developed an algorithm that uses information already collected to “guess” what comes next.
“We realised that, because you are building up a map as you go along, you can use it like a database to predict the environment in unknown areas,” Lee told New Scientist. “Once you have that prediction, you can either save time and not look, or explore anyway and get a more accurate map.”
Posts Tagged ‘robots’
Mapping educated guesses
Thursday, May 10th, 2007The Future of Robot Ethics
Tuesday, April 24th, 2007“Robot technology is accelerating with applications in the home, in the workplace and in the military. It is hard to keep up and we are at a point where the public need to make some informed decisions about our future,” says Professor Noel Sharkey.“Some researchers believe that robots will have consciousness on a timescale of 50+ years while others believe this is a fairytale. The problem is that robots may be required to make decisions that could affect our lives much sooner. While some governments are beginning to draw up ethical guidelines, we need to initiate proper public consultation and informed public debate now.”
The Next Step Was Training Robot Psychologists
Sunday, February 25th, 2007The project involves building a series of robots that can take sensory input from the humans they are interacting with and then adapt their behaviour accordingly.Dr Canamero likens the robots to babies that learn their behaviour from the patterns of movement and emotional state of the world around them.
The robots themselves are simple machines – and in some cases they are off-the-shelf machines. The most interesting aspect of the project is the software.
Dr Canamero said: “We will use very simple robots as the hardware, and for some of the machines we will build expressive heads ourselves.
“We are most interested in programming and developing behavioural capabilities, particularly in social and emotional interactions with humans.”
The robots will learn from the feedback they receive from humans.
“It’s mostly behavioural and contact feedback.
“Tactile feedback and emotional feedback through positive reinforcement, such as kind words, nice behaviour or helping the robot do something if it is stuck.”
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“One of the things we are going to use to detect expressions in faces and patterns in motion is a (artificial) neural network.”
Artificial neural networks are being used because they are very useful for adapting to changing inputs – in this case detecting patterns in behaviour, voice, movement etc.
“Neural networks learn patterns from examples of observation,” said Dr Canamero.
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“It is very important to detect when the human user is angry and the robot has done something wrong or if the human is lonely and the robot needs to cheer him or her up.
“We are focusing on emotions relevant to a baby robot that has to grow and help human with every day life.”
One of the first robots built in the project is exhibiting imprinted behaviour – which is found among birds and some mammals when born.
Designing Robotic Evolution
Saturday, February 24th, 2007Robots that artificially evolve ways to communicate with one another have been demonstrated by Swiss researchers. The experiments suggest that simulated evolution could be a useful tool for those designing of swarms of robots.Roboticists Dario Floreano, Sara Mitri, and Stéphane Magnenat at the Swiss Federal Institute of Technology in Lausanne collaborated with biologist Laurent Keller from the University of Lausanne.
They first evolved colonies of robots in software then tested different strategies on real bots. Both simulated and real robots were set loose in an arena containing two types of objects – one classified as “food” and another designated “poison” – both lit up red.
Each bot had a built-in attraction to food and aversion to poison. They also have a randomly-generated set of parameters, dubbed “genomes” that define the way they move, process sensory information, and how they flash their own blue lights.
“They start with completely random behaviour,” Keller explains. “All they can do is discriminate food from poison.” The robots can see both food or poison from a distance of several metres but can only tell them apart when almost touching.
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Further experiments involving real robots will be used to investigate ways that evolution could be used as a practical design tool. Keller also plans to test what happens when evolved and un-evolved bots mix.
A glimpse at our cyborg future
Friday, February 9th, 2007A robotic exoskeleton controlled by the wearer’s own nervous system could help users regain limb function, which is encouraging news for people with partial nervous system impairment, say University of Michigan researchers.The ankle exoskeleton developed at U-M was worn by healthy subjects to measure how the device affected ankle function. The U-M team has no plans to build a commercial exoskeleton, but their results suggest promising applications for rehabilitation and physical therapy, and a similar approach could be used by other groups who do build such technology.
“This could benefit stroke patients or patients with incomplete injuries of the spinal cord,” said Daniel Ferris, associate professor in movement science at U-M. “For patients that can walk slowly, a brace like this may help them walk faster and more effectively.”
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Typically, robotic rehabilitative devices are worn by patients so that the limb is moved by the brace, which receives its instructions from a computer. Such devices use repetition to help force a movement pattern.
The U-M robotic exoskeleton works the opposite of these rehabilitation aids. In the U-M device, electrodes were attached to the wearer’s leg and those electrical signals received from the brain were translated into movement by the exoskeleton.
“The (artificial) muscles are pneumatic. When the computer gets the electrical signal from the (wearer’s) muscle, it increases the air pressure into the artificial muscle on the brace,” Ferris said. “Essentially the artificial muscle contracts with the person’s muscle.”
Initially the wearer’s gait was disrupted because the mechanical power added by the exoskeleton made the muscle stronger. However, in a relatively short time, the wearers adapted to the new strength and used their muscles less because the exoskeleton was doing more of the work. Their gait normalized after about 30 minutes.
