28 research outputs found
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Development of a minimalistic pneumatic quadruped robot for fast locomotion
In this paper, we describe the development of the
quadruped robot ”Ken” with the minimalistic and lightweight
body design for achieving fast locomotion. We use McKibben
pneumatic artificial muscles as actuators, providing high frequency
and wide stride motion of limbs, also avoiding problems
with overheating. We conducted a preliminary experiment,
finding out that the robot can swing its limb over 7.5 Hz
without amplitude reduction, nor heat problems. Moreover, the
robot realized a several steps of bouncing gait by using simple
CPG-based open loop controller, indicating that the robot can
generate enough torque to kick the ground and limb contraction
to avoid stumbling.This work was partially supported by KAKENHI 23220004, KAKENHI
24000012 and KAKENHI 23700233.This is the accepted manuscript. The final version is available at http://dx.doi.org/10.1109/ROBIO.2012.6490984
Robots that can adapt like animals
As robots leave the controlled environments of factories to autonomously
function in more complex, natural environments, they will have to respond to
the inevitable fact that they will become damaged. However, while animals can
quickly adapt to a wide variety of injuries, current robots cannot "think
outside the box" to find a compensatory behavior when damaged: they are limited
to their pre-specified self-sensing abilities, can diagnose only anticipated
failure modes, and require a pre-programmed contingency plan for every type of
potential damage, an impracticality for complex robots. Here we introduce an
intelligent trial and error algorithm that allows robots to adapt to damage in
less than two minutes, without requiring self-diagnosis or pre-specified
contingency plans. Before deployment, a robot exploits a novel algorithm to
create a detailed map of the space of high-performing behaviors: This map
represents the robot's intuitions about what behaviors it can perform and their
value. If the robot is damaged, it uses these intuitions to guide a
trial-and-error learning algorithm that conducts intelligent experiments to
rapidly discover a compensatory behavior that works in spite of the damage.
Experiments reveal successful adaptations for a legged robot injured in five
different ways, including damaged, broken, and missing legs, and for a robotic
arm with joints broken in 14 different ways. This new technique will enable
more robust, effective, autonomous robots, and suggests principles that animals
may use to adapt to injury
Robust robot bouncing: passive compliance and fexible phase locking
Bouncing is one of the early locomotor milestones in the development of motor skills in human infants. As such, its study should yield insights on the mechanisms underlying the acquisition of motor skills. Goldfield et al. realized a longitudinal study of young infants learning to bounce in a Jolly Jumper. They observed developmental stages (assembly phase, turning phase, phase) that may be typical to infant’s acquisition of motor. To gain a mechanistic view of those stages, we replicated the study using a small humanoid robot (Figure 1, left) suspended to a fixed frame by rubber springs. In human infants, the combination of the Jolly Jumper and the natural compliance of the infant’s musculoskeletal system significantly reduce the dynamic loads of bouncing