Titlebook: RoboCup 2010: Robot Soccer World Cup XIV; Javier Ruiz-del-Solar,Eric Chown,Paul G. Plöger Conference proceedings 2011 Springer Berlin Heid

整顿

Learning Footstep Prediction from Motion Capturethe central pattern generator. We used motion capture data recorded from walking robots to estimate the parameters of the prediction model and to verify the accuracy of the predicted footstep locations. We achieved a precision with a mean error of 1.3cm.

exorbitant

bibliophile

Towards Semantic Scene Analysis with Time-of-Flight Camerasnd b) apply a randomized algorithm for detecting shapes such as planes, spheres, and cylinders. We present experimental results that show that the robustness against noise and outliers of the underlying RANSAC paradigm allows for segmenting and classifying objects in 3D ToF camera data captured in natural mobile manipulation setups.

BOLT

先行

A Review of Shape Memory Alloy Actuators in Roboticsemory effect of these materials will present. Then an assessment of done researches in application of these materials in robots’ structure will accomplish and is devoted to the following area of robotics: Crawler, jumper, flower, fish, walker, medical and Bio-mimetic robotic hand.

暴发户

ADORN

0302-9743 ceedings of the 14th RoboCup International Symposium, held in Singapore, in June, 2010 - representing the scientific tracks structured in four sessions entitled simulation and rescue robots; robot perception and localization; robot motion and humanoid robots; and human robot interaction and semantic

植物茂盛

Entropy-Based Active Vision for a Humanoid Soccer Robot world state estimate through minimizing the entropy of an underlying particle distribution. Being originally computationally expensive, this approach is optimized to become executable in real-time on a robot with limited resources. We demonstrate the approach on a humanoid robot, performing self-lo

收集

A Realistic Simulation Tool for Testing Face Recognition Systems under Real-World Conditionsand real face and background images taken under real-world conditions with different acquisition angles. Inside the simulated environment, an observing agent, the one with the ability to recognize faces, can navigate and observe the real face images, at different distances, angles and with indoor or

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