Low-level Autonomy of the Humanoid Robots H6 & H7

Bipedal humanoid robots are intrinsically unstable against unforeseen perturbations. Conventional zero moment point (ZMP)-based locomotion algorithms can reject perturbations by incorporating sensory feedback, but they are less effective than the dynamic full body behaviors humans exhibit when pushed. Recently, a number of biomechanically motivated push recovery behaviors have been proposed that can handle larger perturbations. However, these methods are based upon simplified and transparent dynamics of the robot, which makes it suboptimal to implement on common humanoid robots with local position-based controllers. To address this issue, we propose a hierarchical control architecture. Three low-level push recovery controllers are implemented for position controlled humanoid robots that replicate human recovery behaviors. These low-level controllers are integrated with a ZMP-based walk controller that is capable of generating reactive step motions. The high-level controller constructs empirical decision boundaries to choose the appropriate behavior based upon trajectory information gathered during experimental trials. Our approach is evaluated in physically realistic simulations and on a commercially available small humanoid robot.

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Self-Learning Low-Level Controllers

10.5772/intechopen.96732 ◽

2021 ◽

Author(s):

Dang Xuan Ba ◽

Joonbum Bae

Keyword(s):

Sliding Mode ◽

Humanoid Robots ◽

Nonlinear Functions ◽

Low Level ◽

Unstructured Environments ◽

Learning Rules ◽

Whole Systems ◽

Self Learning ◽

Control Criterion ◽

Adaptation Ability

Humanoid robots are complicated systems both in hardware and software designs. Furthermore, the robots normally work in unstructured environments at which unpredictable disturbances could degrade control performances of whole systems. As a result, simple yet effective controllers are favorite employed in low-level layers. Gain-learning algorithms applied to conventional control frameworks, such as Proportional-Integral-Derivative, Sliding-mode, and Backstepping controllers, could be reasonable solutions. The adaptation ability integrated is adopted to automatically tune proper control gains subject to the optimal control criterion both in transient and steady-state phases. The learning rules could be realized by using analytical nonlinear functions. Their effectiveness and feasibility are carefully discussed by theoretical proofs and experimental discussion.

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Efficient reaching motion planning method for low-level autonomy of teleoperated humanoid robots

Advanced Robotics ◽

10.1080/01691864.2013.876931 ◽

2014 ◽

Vol 28 (7) ◽

pp. 433-439 ◽

Cited By ~ 9

Author(s):

Fumio Kanehiro ◽

Eiichi Yoshida ◽

Kazuhito Yokoi

Keyword(s):

Motion Planning ◽

Humanoid Robots ◽

Planning Method ◽

Low Level

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BIOLOGICALLY BASED TOP-DOWN ATTENTION MODULATION FOR HUMANOID INTERACTIONS

International Journal of Humanoid Robotics ◽

10.1142/s0219843608001285 ◽

2008 ◽

Vol 05 (01) ◽

pp. 3-24 ◽

Cited By ~ 14

Author(s):

JAN MORÉN ◽

ALEŠ UDE ◽

ANSGAR KOENE ◽

GORDON CHENG

Keyword(s):

Visual Perception ◽

Humanoid Robots ◽

Dependent Manner ◽

Early Vision ◽

Top Down ◽

Bottom Up ◽

Low Level ◽

Perception System ◽

Meaningful Context ◽

Context Dependent

An adaptive perception system enables humanoid robots to interact with humans and their surroundings in a meaningful context-dependent manner. An important foundation for visual perception is the selectivity of early vision processes that enables the system to filter out low-level unimportant information while attending to features indicated as important by higher-level processes by way of top-down modulation. We present a novel way to integrate top-down and bottom-up processing for achieving such attention-based filtering. We specifically consider the case where the top-down target is not the most salient in any of the used submodalities.

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Tryptophan-Niacin Metabolism in Rat with Puromycin Aminonucleoside-Induced Nephrosis

International Journal for Vitamin and Nutrition Research ◽

10.1024/0300-9831.76.1.28 ◽

2006 ◽

Vol 76 (1) ◽

pp. 28-33 ◽

Cited By ~ 7

Author(s):

Yukari Egashira ◽

Shin Nagaki ◽

Hiroo Sanada

Keyword(s):

Body Weight ◽

Urinary Excretion ◽

Enzyme Activities ◽

Treated Group ◽

Control Group ◽

Puromycin Aminonucleoside ◽

Low Level ◽

Key Enzyme

We investigated the change of tryptophan-niacin metabolism in rats with puromycin aminonucleoside PAN-induced nephrosis, the mechanisms responsible for their change of urinary excretion of nicotinamide and its metabolites, and the role of the kidney in tryptophan-niacin conversion. PAN-treated rats were intraperitoneally injected once with a 1.0% (w/v) solution of PAN at a dose of 100 mg/kg body weight. The collection of 24-hour urine was conducted 8 days after PAN injection. Daily urinary excretion of nicotinamide and its metabolites, liver and blood NAD, and key enzyme activities of tryptophan-niacin metabolism were determined. In PAN-treated rats, the sum of urinary excretion of nicotinamide and its metabolites was significantly lower compared with controls. The kidneyα-amino-β-carboxymuconate-ε-semialdehyde decarboxylase (ACMSD) activity in the PAN-treated group was significantly decreased by 50%, compared with the control group. Although kidney ACMSD activity was reduced, the conversion of tryptophan to niacin tended to be lower in the PAN-treated rats. A decrease in urinary excretion of niacin and the conversion of tryptophan to niacin in nephrotic rats may contribute to a low level of blood tryptophan. The role of kidney ACMSD activity may be minimal concerning tryptophan-niacin conversion under this experimental condition.

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