A walking robot goes mountaineering

Jul 13, 2007

The human gait is a marvel of coordination. All aspects of movement control – from the angle of the knee joints to the momentum of the hip up to the balance point of the torso – need to be meticulously adjusted. In addition, the gait is adaptable to different environments. Walking on ice is different from walking on solid ground, walking uphill is different from downhill.

In their study, publishing in PLoS Computational Biology July 13, 2007, scientists around Florentin Wörgötter, Bernstein Center for Computational Neuroscience at the University of Göttingen, have simulated the neuronal principles that form the basis of this adaptivity in a walking robot.

"RunBot", as it is called, lives up to its name – it holds the world record in speed walking for dynamic machines. Now its inventors have expanded its repertoire.

With an infrared eye it can detect a slope on its path and adjust its gait on the spot. Just as a human, it leans forwards slightly and uses shorter steps. It can learn this behavior using only a few trials.

The robots ability to abruptly switch from one gait to the other is due to the hierarchical organization of the movement control. In this respect, it resembles that of a human and can hold as a human model. On the lower hierarchical levels, movement is based on reflexes driven by peripheral sensors. Control circuits ensure that the joints are not overstretched or that the next step is initiated as soon as the foot touches the ground.

Only when the gait needs to be adapted, higher centers of organization step in – a process triggered by the human brain or, in case of the robot, by its infrared eye leading on to a simpler neural network. Because of the hierarchical organization adjustment of the gait can be achieved by changing only a few parameters. Other factors will be automatically tuned through the regular circuits.

At its first attempt to climb a slope, RunBot will fall over backwards, as it has not yet learned to react to its visual input with a change in gait. But just like children, RunBot learns from its failures, leading to a strengthening of the contact between the eye and the sites of movement control. Only once these connections are established, step length and body posture are controllable by the visually induced signal. The steeper the slope, the stronger RunBot will adapt its gait.

Source: Public Library of Science

Explore further: Project launched to study evolutionary history of fungi

add to favorites email to friend print save as pdf

Related Stories

Amber 2 robot walks with a human gait (w/ Video)

Oct 25, 2013

(Phys.org) —The engineering team at Texas A&M's Amber robotics labs has been hard at work trying to improve one area of robotics that others seem to be ignoring—getting a robot to mimic the natural gait ...

Engineering an affordable exoskeleton

Jun 12, 2014

When soccer's World Cup—the most-watched sports event on Earth—kicks off June 12, Berkeley professor Homayoon Kazerooni and his research assistants won't be watching the players. They'll be staring at ...

Recommended for you

Project launched to study evolutionary history of fungi

2 hours ago

The University of California, Riverside is one of 11 collaborating institutions that have been funded a total of $2.5 million by the National Science Foundation for a project focused on studying zygomycetes – ancient li ...

Pakistan releases smuggled turtles into the wild

3 hours ago

Pakistani officials and environmentalists on Monday released some 200 rare turtles into the River Indus after the reptiles were retrieved from a southwestern Chinese town where they were seized by customs ...

Different watering regimes boost crop yields

6 hours ago

Watering tomato plants less frequently could improve yields in saline conditions, according to a study of the impact of water and soil salinity on vegetable crops.

User comments : 0