scholarly journals A COMPUTATIONAL FRAMEWORK OF GOAL DIRECTED VOLUNTARY MOTION GENERATION AND CONTROL LOOP IN HUMANOID ROBOTS

2021 ◽  
Author(s):  
Evren DAĞLARLI
Keyword(s):  
Humanoid Robots ◽  
Control Loop ◽  
Motion Generation ◽  
Computational Framework ◽  
Voluntary Motion ◽  
And Control

scholarly journals Turning Gait Planning Method for Humanoid Robots

2018 ◽  
Vol 8 (8) ◽  
pp. 1257 ◽  
Author(s):  
Tianqi Yang ◽  
Weimin Zhang ◽  
Xuechao Chen ◽  
Zhangguo Yu ◽  
Libo Meng ◽  
...  
Keyword(s):  
Inverted Pendulum ◽  
Center Of Mass ◽  
Translational Motion ◽  
Humanoid Robots ◽  
Inverted Pendulum Model ◽  
Straight Line ◽  
Pendulum Model ◽  
The Stability ◽  
And Control ◽  
Present Simulation

The most important feature of this paper is to transform the complex motion of robot turning into a simple translational motion, thus simplifying the dynamic model. Compared with the method that generates a center of mass (COM) trajectory directly by the inverted pendulum model, this method is more precise. The non-inertial reference is introduced in the turning walk. This method can translate the turning walk into a straight-line walk when the inertial forces act on the robot. The dynamics of the robot model, called linear inverted pendulum (LIP), are changed and improved dynamics are derived to make them apply to the turning walk model. Then, we expend the new LIP model and control the zero moment point (ZMP) to guarantee the stability of the unstable parts of this model in order to generate a stable COM trajectory. We present simulation results for the improved LIP dynamics and verify the stability of the robot turning.

Study on the Motion Generation Method of Gun Training Simulator

2012 ◽  
Vol 182-183 ◽  
pp. 1673-1680
Author(s):  
Yu Wang ◽  
Ri Na Su
Keyword(s):  
Real Time ◽  
Driving Force ◽  
Motion Simulation ◽  
Motion Generation ◽  
Motion Platform ◽  
Training Simulator ◽  
Simulation Experiments ◽  
Optimize Design ◽  
Homogeneous Matrix ◽  
And Control

A kind of 3-RPS and 3-DOF parallel robotic mechanisms is used as motion-sensible-platform of gun training simulator to implement the motion simulation. Its dynamics is analyzed and driving force of joint is gained. This paper introduces the study on motion generation of gun training simulator. The moving model of gun is established on the basis of the model of vehicle. We solve the pose of gun by applying the theory of homogeneous matrix. In order to ensure actuators moving at a preset speed and enable the motion-sensible-platform to perform a real-time moving posture simulation of a wheeled gun vehicle in running, the speed equation of actuator is given. The feasibility of models was tested through the simulation experiments. All of these works are beneficial to optimize design and control realization of motion platform structure.

scholarly journals Embodied intelligence via learning and evolution

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Agrim Gupta ◽  
Silvio Savarese ◽  
Surya Ganguli ◽  
Li Fei-Fei
Keyword(s):  
Intelligent Control ◽  
Energy Efficient ◽  
Large Scale ◽  
Complex Environments ◽  
Environmental Complexity ◽  
Baldwin Effect ◽  
Computational Framework ◽  
Mechanistic Basis ◽  
Embodied Intelligence ◽  
And Control

AbstractThe intertwined processes of learning and evolution in complex environmental niches have resulted in a remarkable diversity of morphological forms. Moreover, many aspects of animal intelligence are deeply embodied in these evolved morphologies. However, the principles governing relations between environmental complexity, evolved morphology, and the learnability of intelligent control, remain elusive, because performing large-scale in silico experiments on evolution and learning is challenging. Here, we introduce Deep Evolutionary Reinforcement Learning (DERL): a computational framework which can evolve diverse agent morphologies to learn challenging locomotion and manipulation tasks in complex environments. Leveraging DERL we demonstrate several relations between environmental complexity, morphological intelligence and the learnability of control. First, environmental complexity fosters the evolution of morphological intelligence as quantified by the ability of a morphology to facilitate the learning of novel tasks. Second, we demonstrate a morphological Baldwin effect i.e., in our simulations evolution rapidly selects morphologies that learn faster, thereby enabling behaviors learned late in the lifetime of early ancestors to be expressed early in the descendants lifetime. Third, we suggest a mechanistic basis for the above relationships through the evolution of morphologies that are more physically stable and energy efficient, and can therefore facilitate learning and control.

Optimizing anaerobic co-digestion plants: MIR online instrumentation and dynamic real-time substrate feed optimization

2015 ◽  
Vol 63 (7) ◽  
Author(s):  
Daniel Gaida ◽  
Christian Wolf ◽  
Robin Eccleston ◽  
Michael Bongards
Keyword(s):  
Predictive Control ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Control Loop ◽  
Loop Control ◽  
Plant Operation ◽  
Novel Approaches ◽  
The One ◽  
Middle Infrared ◽  
And Control

AbstractClosed-loop control of the substrate feed as well as the application of online instrumentation are important to achieve optimal biogas plant operation. Therefore, this paper presents two novel approaches for online instrumentation and control to achieve optimal AD plant operation based on middle-infrared spectroscopy on the one hand and nonlinear model predictive control on the other hand. At present, research into both techniques is being performed separately, with the intention that in the future the spectroscopic measurements will be integrated into the control loop.

Supervoxel Plane Segmentation and Multi-Contact Motion Generation for Humanoid Stair Climbing

2017 ◽  
Vol 14 (01) ◽  
pp. 1650022 ◽  
Author(s):  
Tianwei Zhang ◽  
Stéphane Caron ◽  
Yoshihiko Nakamura
Keyword(s):  
Motion Planning ◽  
Humanoid Robot ◽  
Real Life ◽  
Estimation Method ◽  
Humanoid Robots ◽  
Stair Climbing ◽  
Lidar Data ◽  
Motion Generation ◽  
Prior Models ◽  
Motion Generator

Stair climbing is still a challenging task for humanoid robots, especially in unknown environments. In this paper, we address this problem from perception to execution. Our first contribution is a real-time plane-segment estimation method using Lidar data without prior models of the staircase. We then integrate this solution with humanoid motion planning. Our second contribution is a stair-climbing motion generator where estimated plane segments are used to compute footholds and stability polygons. We evaluate our method on various staircases. We also demonstrate the feasibility of the generated trajectories in a real-life experiment with the humanoid robot HRP-4.

Humanoid Robots and Control

2016 ◽  
pp. 15-47
Author(s):  
Adam Spiers ◽  
Said Ghani Khan ◽  
Guido Herrmann
Keyword(s):  
Humanoid Robots ◽  
And Control

Aeroelastic Vehicle Sensor Placement for Feedback Control Applications Using Gain Stability

2000 ◽  
Author(s):  
Abdul G. Al-Shehabi ◽  
Brett Newman
Keyword(s):  
Flight Control ◽  
Optimization Method ◽  
Stability Criteria ◽  
Control Loop ◽  
Aircraft Structure ◽  
Design Constraints ◽  
Optimal Approach ◽  
And Control ◽  
Vehicle Sensor ◽  
Structural Mode

Abstract Optimal positions for aeroelastic vehicle feedback sensors, which meet design constraints and control requirements, are difficult to determine. This paper introduces a systematic and optimal approach for choosing sensor locations based on gain stability criteria. A steepest descent optimization method with constraints is used to minimize such objective criteria, which are based on the dipole magnitudes for each aeroelastic mode appearing in a traditional Evans diagram for a scalar control loop. Each dipole magnitude term is multiplied by a weight parameter. Rigid-body augmentation characteristics are implicitly accounted for in the type of input-output pairs utilized and in predefined loop compensation structure. Constraints enforcing minimum phase zeros in the transfer function are also considered. A flexible aircraft structure is used as an example to demonstrate this procedure. Results indicate flight control and structural mode control characteristics can be effectively balanced.

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