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检索条件"机构=Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications"

共 87 条记录，以下是41-50 订阅

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Research on Smooth Movement Control and Testing of a Wheeled-Legged Robot

Research on Smooth Movement Control and Testing of a Wheeled...

引用

IEEE International Conference on Mechatronics and Automation

作者： Jingyu Wang Daming Li Zhijun Zhao Wang Jie Yaobing Wang Junkai Sun Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

This paper focuses on the application of wheeledlegged robots for extraterrestrial exploration. To address the stability and terrain adaptability issues during planetary surface exploration, a novel motion control strategy integrating body attitude control and support force control is proposed based on kinematic inverse solution. This strategy adjusts the body posture by dynamically regulating the length of each leg to ensure sufficient wheel-ground contact force while traversing rough terrains. The paper also conducts simulation and tests of the wheeled-legged robot in typical terrains. Results demonstrate that the proposed algorithm effectively overcomes terrain variations and enhances stability during the robot's movement.

关键词： Legged locomotion Attitude control Force Wheels Kinematics Stability analysis Surface roughness

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An Approach on Visual Detecting Multi-Targets in the Unstructured and Complex Scenes Based on RGB-D Images 5

An Approach on Visual Detecting Multi-Targets in the Unstruc...

引用

5th International Conference on Automation, Control and robotics Engineering, CACRE 2020

作者： Tan, Qimeng Sun, Yikun Xin, Pengfei Lin, Yimin Ma, Chao Wang, Xinyu Beijing Institute of Spacecraft System Engineering Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing China Beijing Special Engineering Design and Research Institute Propellant Injection Laboratory Beijing China Beijing University of Posts Telecommunications Institute of Optical Communication Optoelectronics Beijing China Beijing Information Science and Technology University School of Instrument Science and Optoelectronic Engineering Beijing China

ISBN: (纸本)9781728198880

The technology of detecting and identifying multitarget is of significance for robotic visual navigation within the unknown, unstructured, complex scenes, whose result could be considered as important references of 3D map building and path planning for mobile robot. Traditional algorithms of target detection can be applied to 2D images without depth information generally, which is disturbed by few factors such as illumination, view and scale easily. Therefore, an approach on visual detecting multi-target of unstructured and complex scenes based on RGBD images is proposed in this article to solve the above problem, which is composed of extracting descriptor of rotation and scale invariance feature, local encoding of targets, random ferns classifier training, Hough map generation, Hough voting theoretical model and local maximum search. Experimental results have shown that the proposed approach reduce the calculation of extracting and matching local feature, improve the accuracy of object recognition and detection in unknown complex environments, be capable of well robust against few disturbing factors i.e. rotation, scale, illumination, occlusion and non-rigid body deformation. © 2020 IEEE.

关键词： Motion planning

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Landing Performance Simulation of an Asteroid Landing Mechanism

Landing Performance Simulation of an Asteroid Landing Mechan...

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IEEE International Conference on Information and Automation

作者： Zhijun Zhao Delun Li Baofeng Yuan Sheng Gao Jingdong Zhao Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering State Key Laboratory of Robotics and System Harbin Institute of Technology

ISBN: (纸本)9781467391054

Asteroid landing is a new research field in deep space exploration, which has important scientific and economic values in learning the origin of the solar system and exploring the asteroid. It is microgravity and little media properties are obtained on the asteroid surface, thus good landing performance is demanded to realize safe landing of the landing mechanism. Landing mechanism in the paper has three legs, and the damping device is located between the landing gear and the equipment base. Simulation method is introduced to analyze the landing performance of the landing mechanism. Landing performance of the landing mechanism on 30° landing slope with the largest landing velocity is simulated in three typical landing modes, and the landing performance is reflected by stability time of the landing gear and overloading acceleration of the equipment base. Landing simulation has important significance in learning landing performance and guiding the landing of the landing mechanism.

关键词： Asteroid Landing mechanism Landing performance Simulation

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Compound Asynchronous Exploration and Exploitation

Compound Asynchronous Exploration and Exploitation

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2019 2nd International Conference on Mechanical,Electronic and Engineering technology(MEET 2019)

作者： Jie Bai Li Liu Yaobing Wang Haoyu Zhang Jianfei Li Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering College of Engineering Peking University Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering

Data efficiency has always been a significant key topic for deep reinforcement learning. The main progress has been on sufficient exploration and effective exploitation. However, the two are often discussed separately. Profit from distributed systems, we propose an asynchronous approach to deep reinforcement learning by combining exploration and exploitation. We apply our framework to off-the-shelf deep reinforcement learning algorithms, and experimental results show that our algorithm is superior in final performance and efficiency.

关键词： Deep Reinforcement Learning Exploration and Exploitation Asynchronous Methods

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The current feedforward compensation method for the cogging torque of permanent magnet synchronous motors

The current feedforward compensation method for the cogging ...

引用

IEEE International Conference on Cyber technology in Automation, Control, and intelligent systems

作者： Liu Xin Zhou Dong Zhang Pei Wang Rui Beijing Institute of Spacecraft System Engineering Beijing Key Laboratory of Intelligent Space Robotic System Technology and Applications Beijing PR China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

The cogging torque is the inherent characteristic of permanent motors with the cogging. The cogging torque reduces the stability of the motor, especially in the status of the low speed. A compensation method based on the current feedforward is proposed in terms with the function between the torque and Q-Current by the method of space Vector PWM of the permanent magnet synchronous motors. The relation equation between the cogging torque and the rotor angle is obtained by the experimental analysis. And then, the transfer function of the current closed-loop system is obtained by using the experiment data and the system identification method. The cogging torque compensation current is calculated by the forecast for the position of the rotor. The experiment results show that the presented method can effectively improve the stability of the motor speed.

关键词： Torque Forging Permanent magnet motors Synchronous motors Rotors Transfer functions Feedforward systems

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Energy-Consumption Optimization Control for Lunar Rover's Travel with Torque-Distribution-strategy in Rear Wheels

Energy-Consumption Optimization Control for Lunar Rover's Tr...

引用

IEEE International Conference on Control Science and systems Engineering (CCSSE)

作者： Delun Li Jianfei Cao Yiliang Chen Zongwu Xie State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing China

ISBN: (数字)9798331517199

ISBN: (纸本)9798331517205

In anticipation of future extensive lunar surface operations, lunar rovers are required to advance towards higher speeds and improved energy conservation. When traveling at high speeds on the lunar surface, the vehicle's energy expenditure is greatly amplified by the influence of the terrain, particularly in conditions where driving and steering are coupled. This paper proposes an energy-saving control strategy for lunar rovers that employs dynamic rear-axle torque distribution, with the goal of optimizing transient energy consumption during travel. To tackle the challenge of non-differentiable functions within the optimization objectives, we suggest using a zeroth-order gradient optimization method for resolution, dynamically constraining the range of control parameters to fulfill the dynamic torque distribution objectives as needed for the task. The energy-saving control effectiveness of the algorithm has been confirmed through simulation, demonstrating a minimum energy-saving ratio of at least 4%, which increases to over 11% as the speed level rises, offering a valuable technical solution for the energy optimization of lunar rovers.

关键词： space vehicles Energy consumption Torque Distribution strategy Moon Wheels Optimization methods systems engineering and theory Vehicle dynamics Transient analysis

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Lunar Rover's Path Tracking Control Strategy Using Zero-Order Optimization Method

Lunar Rover's Path Tracking Control Strategy Using Zero-Orde...

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IEEE International Conference on Control Science and systems Engineering (CCSSE)

作者： Jianfei Cao Yaobing Wang Jiyang Yu Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing China Beijing Institute of Spacecraft System Engineering Beijing China

ISBN: (数字)9798331517199

ISBN: (纸本)9798331517205

The development of lunar rovers is critical for human exploration of the lunar surface. These rovers will need to travel longer distances at higher speeds, and the efficient control of their paths is essential for mission success. Model Predictive Control (MPC) is a path tracking method with foresight and robustness, capable of predicting vehicle movement and solving optimization problems to minimize cost functions. However, the complexity of lunar environments necessitates simplified models, such as kinematic models, to reduce computational cost. The study proposes a special MPC method that uses zeroth-order gradient optimization to directly solve the nonlinear model and generate precise control commands, significantly reducing computational burden and meeting the computational cost requirements of lunar rover control.

关键词： space vehicles Tracking Computational modeling Moon Optimization methods Kinematics Predictive models Robustness Computational efficiency Predictive control

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Virtual Constraint Based Adaptive Control for Biped Robot with Speed Regulation

Virtual Constraint Based Adaptive Control for Biped Robot wi...

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IEEE International Conference on Mechatronics and Automation

作者： Jianfei Li Yaobing Wang Dawei Zhang Li Liu Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing China Center of Excellence for Intelligent Mechanical Systems College of Engineering Peking University Beijing China

ISBN: (纸本)9781509023974

The Virtual Holonomic Constraint (VHC) approach, with its flexibility and stability, is drawing more attentions in generating gait for biped robots. This paper generalizes the VHC approach by adding other variables such as walking speed to the constraint functions. The robot is able to walk up or down along slopes with commanded speeds, and more importantly, allows it to walk continuously and steadily in varying surfaces. In addition, the control approach named Partial Decoupling Control is used to implement the VHC, which at the first time equips the VHC approach with the parameter adaptation laws which significantly improves the stability and performance of the systems. Full dynamics simulations with a five-bar planar robot are used to illustrate the effectiveness of the proposed approach.

关键词： adaptive control virtual constraints VHC biped robot speed regulation

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Semantic and Neighborhood Preserving Dictionar Learning for Symmetric Positive-Definite Matrice

Semantic and Neighborhood Preserving Dictionar Learning for ...

引用

2016 IEEE 13th International Conference on Signal Processing（ICSP2016）

作者： Daming Li Lei Chen Fei Wang The School of Electronic and Information Engineering Xi’an Jiaotong University Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering

The symmetric positive-definite(SPD) matrices form a Riemannian manifold, and sparse representation on the SPD matrix manifold has received increasingly attentions recently. In this paper, we propose a semantic and neighborhood preserving dictionary learning method for the sparse representation on the SPD matrix manifold. The semantic preserving ensures that the semantic similarity information can be kept while sparse representation, and the neighborhood preserving is introduced to better reflect the geometrical structure of the manifold. To effectively model the semantic similarity of the SPD matrices and the geometrical structure, a Laplacian smooth operator is incorporated into the objective function of dictionary *** the learned dictionary, the obtained sparse representations of SPD matrices are more discriminative. Experimental results on publicly available datasets demonstrate the effectiveness of the proposed method.

关键词： Dictionary learning symmetric positive-definite matrix sparse representation Riemannian manifold

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Learning a Faster Locomotion Gait for a Quadruped Robot with Model-Free Deep Reinforcement Learning

Learning a Faster Locomotion Gait for a Quadruped Robot with...

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IEEE International Conference on robotics and Biomimetics

作者： Biao Hu Shibo Shao Zhengcai Cao Qing Xiao Qunzhi Li Chao Ma College of Information Science and Technology Beijing University of Chemical Technology Beijing China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing China

Quadruped robots have great agility, flexibility and stability, which enables them to walk through uneven terrain. Motion control of legged robots is always a difficult problem. Previous approaches mostly either use a predefined gait that results in clumsy and unnatural behavior, or use reinforcement learning approach to generate a gait strategy that needs longtime computation and elegant network design. In this paper, we present an effective approach that uses deep reinforcement learning with prior knowledge to optimize the gait of quadruped robot. By using a specific quadruped robot walking gait as a priori knowledge, this approach adopts the technique of distributed proximal policy optimization to optimize the search for better gait. The proposed approach does not require modelling of complex robots, and has good network convergence speed and learning effect. Simulation results demonstrate that our proposed approach converges faster than other deep reinforcement learning methods without prior knowledge. Besides, our achieved gait has higher speed that is 50% faster than the trot gait without optimization.

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