scholarly journals Trajectory planning of the nursing robot based on the center of gravity for aluminum alloy structure

2021 ◽  
Vol 60 (1) ◽  
pp. 731-743
Author(s):  
Libo Zhang ◽  
Hanjun Gao ◽  
Huichao Xu ◽  
Jing Song
Keyword(s):  
Trajectory Planning ◽  
Inverse Kinematics ◽  
Center Of Pressure ◽  
Pressure Sensors ◽  
Center Of Gravity ◽  
Robot Arm ◽  
Planning Algorithm ◽  
Movement Stability ◽  
The Stability ◽  
The Mathematical Model

Abstract In this paper, the robot arm is manufactured to increase the structural strength and improve safety. The stability of the nursing robot in the process of carrying out the typical nursing task of holding patients was studied, and the influence of the center of gravity on the movement stability of the nursing robot was analyzed. The mathematical model of the stability of the robot is built by using the inverse kinematics solution of the robot. By studying the trajectory planning of a nursing robot under the condition of ZMP constraint, the robot can move safely and optimally along the prescribed trajectory between two working points. The simulation results show that the algorithm can significantly improve the work safety of the robot. In the experiment, four pressure sensors are used to measure the pressure of four wheels on the ground, the data are obtained and substituted into the expression of center of pressure (COP) method. The results show that the stability is in a reasonable moving area without any hidden danger, and its COP value is less than the stable qualitative boundary, which verifies the rationality and effectiveness of the optimal center of gravity stability planning algorithm.

The Research of Neural-Fuzzy Inference System Model for Arm of Excavator Robot

2010 ◽  
Vol 143-144 ◽  
pp. 1352-1357 ◽  
Author(s):  
Fu Bin Wang ◽  
Jie Liu ◽  
Zhi Kun Chen ◽  
Da Meng Guo
Keyword(s):  
Trajectory Planning ◽  
Fuzzy Inference System ◽  
Inverse Kinematics ◽  
Joint Angle ◽  
Fuzzy Inference ◽  
Robot Arm ◽  
Inverse Mapping ◽  
Inference System ◽  
Working Device ◽  
Neural Fuzzy

To improve the trajectory planning control accuracy of the working device of excavator robot when working for excavation, reduce working device of excavator robot to be the two joints two dimension robot arm composed of arm and bucket when analyses. Creating inverse kinematics model, need to relate to terminal position and orientation space of bucket and joint space and cylinder space of working devices to plan trace, so that to control excavator robot in each space. Because of the geometry complexity of inverse kinematics, the nonlinear of electro-hydraulic system, the uncertainty and non-uniqueness for inverse mapping, lead to the difficulty of trajectory planning. To improve the precision for tracking desired trace, obtaining inverse kinematics mapping between terminal trace and joint angle, use two adaptive neural-fuzzy inference system(ANFIS) to learn inverse mapping relations between (x, y) two joint coordinate and joint angle, create ANFIS inverse mapping model. Select I/O curve data of inverse mapping to train ANFIS structure, obtain I/O mapping curve of fuzzy model, realize the aim of obtaining corresponding joint angle based on given desired excavation trace. Use the model to trace expected motion trace finally, indicate by simulation that trace precision can meet the actual demands.

scholarly journals Design of a Sweet Potato Transplanter Based on a Robot Arm

2021 ◽  
Vol 11 (19) ◽  
pp. 9349
Author(s):  
Zhengduo Liu ◽  
Xu Wang ◽  
Wenxiu Zheng ◽  
Zhaoqin Lv ◽  
Wanzhi Zhang
Keyword(s):  
Sweet Potato ◽  
Target Detection ◽  
Theoretical Basis ◽  
Inverse Kinematics ◽  
Leakage Rate ◽  
Robot Arm ◽  
Sweet Potatoes ◽  
Transplanting Machine ◽  
Qualification Rate ◽  
The Mathematical Model

Traditional sweet potato transplanters have the problem of seedling leakage and can only accomplish one transplantation method at a time, which does not meet the requirements of complex planting terrain that requires multiple transplantation methods. Therefore, this paper proposes a design for a crawler-type sweet potato transplanting machine, which can accomplish a variety of transplanting trajectories and conduct automatic replanting. The machine has a transplanting piece and a replanting piece. The transplanting piece completes the transplanting action through a transplanting robot arm, and the replanting piece detects the transplanting status by deep learning. The mathematical model of the transplanting robot arm is built, and the transplanting trajectory is inferred from the inverse kinematics model of the transplanting robot. In the replanting piece, a target detection network is used to detect the transplanting status. The DBIFPN structure and the CBAM_Dense attention mechanism are proposed to improve the accuracy of the target detection of sweet potato seedlings. The experiment showed that the transplanting robot arm can transplant sweet potatoes in horizontal and vertical methods, and the highest transplanting qualification rate is 96.8%. Compared with the use of the transplanting piece alone, the leakage rate of the transplanting–replanting mechanism decreased by 5.2%. These results provide a theoretical basis and technical support for the research and development of sweet potato transplanters.

Stability margin for robust walking gaits constructed by center of pressure

2016 ◽  
Vol 32 ◽  
Author(s):  
Kuo-Yang Tu ◽  
Cheng-Hsiung Huang ◽  
Jacky Baltes
Keyword(s):  
Center Of Pressure ◽  
Stability Margin ◽  
Humanoid Robots ◽  
Measuring System ◽  
Gait Stability ◽  
Stability Margins ◽  
Double Support ◽  
Walking Gait ◽  
The Stability ◽  
The Mathematical Model

AbstractUsually, humanoid walking gaits are only roughly distinguished between stable and unstable. The evaluation of a stable humanoid walking gait is difficult to quantify in scales. And, it is extremely hard to adjust humanoid robots in suitable a walking gait for different movement objectives such as fast walking, uneven floor walking, and so on. This paper proposes a stability margin constructed by center of pressure (COP) to evaluate the gait stability of humanoid walking. The stability margin is modeled by the COP regions that a humanoid robot needs for stable standing. We derive the mathematical model for COP position by dividing the walking gait into single and double support phases in order to measure the stability of the COP regions. An actual measuring system for the stable COP regions is designed and implemented. The measured COP trajectory of a walking gait is eventually evaluated with respect to the stable COP regions for the stability margins. The evaluation focuses on weak stability areas to be improved for robust walking gaits. To demonstrate the robustness of the improved walking gait, we replicate the experiment on three different terrains. The experiments demonstrate that the walking gaits developed based on stable COP region can be applied for different movement objectives.

Trajectory Generation of a Biped Locomotive Robot

1990 ◽  
Vol 2 (4) ◽  
pp. 294-302
Author(s):  
Yasuo Kurematsu ◽  
◽  
Shinzo Kitamura
Keyword(s):  
Trajectory Planning ◽  
Inverse Kinematics ◽  
Inverted Pendulum ◽  
A Priori ◽  
Forward Direction ◽  
Center Of Gravity ◽  
Simulation Studies ◽  
The Neural Network ◽  
The World ◽  
Impulsive Disturbances

This paper studies the trajectory planning of a biped locomotive robot from the following standpoints. * Only the position and velocity of the center of gravity of robot in the forward direction for each step are given a priori. * It is supposed that the center of gravity of the robot moves like an inverted pendulum. * The neural network of Hopfield's type solves the inverse kinematics so as to obtain the joint positions in the world coordinate from the positions of the supporting toes and of the center of gravity calculated from the equation of inverted pendulum. * The method was examined by simulation studies. They showed satisfactory results in stationary walking and also the robustness for impulsive disturbances. The proposed method therefore provides a simplified version for the autonomous trajectory planning.

A Study of Topology Optimization Design for the Wafer Handling Robot Arm

2009 ◽  
Vol 626-627 ◽  
pp. 471-476 ◽  
Author(s):  
M. Cong ◽  
T.J. Wang ◽  
Cheng Shuang Zhang
Keyword(s):  
Topology Optimization ◽  
Modal Analysis ◽  
Optimization Design ◽  
Natural Vibration ◽  
Natural Frequencies ◽  
Homogenization Method ◽  
Robot Arm ◽  
Minimum Compliance ◽  
The Stability ◽  
The Mathematical Model

To attain the optimal shape of the robot arm with the minimum compliance and the suitable weight and lower the possibility of vibration, this paper applies the homogenization method to describe the topology optimization design of the wafer handling robot arm which modal analysis is carried out subsequently. We deduce and establish the mathematical model of the topology optimization based on the homogenization method and calculate it by ANSYS. The results suggested that the compliance and the weight were reduced. Then we calculated the modal analysis of the optimized and non-optimized robot arms, and it was found that the first sixth natural frequencies of the optimized robot arm all increased whereas the probability of the natural vibration declined. It is concluded that the topology optimization design of the wafer handling robot has been shown to be effective in improving the stability of the robot arm.

scholarly journals Control system of 4-DOF palletizing robot based on improved R control multi-objective trajectory planning

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110027
Author(s):  
Jianqiang Wang ◽  
Yanmin Zhang ◽  
Xintong Liu
Keyword(s):  
Control System ◽  
Trajectory Planning ◽  
Robot Control ◽  
Machining Process ◽  
Planning System ◽  
Positioning Accuracy ◽  
Multi Objective ◽  
Planning Algorithm ◽  
Function Testing ◽  
Robot Control System

To realize efficient palletizing robot trajectory planning and ensure ultimate robot control system universality and extensibility, the B-spline trajectory planning algorithm is used to establish a palletizing robot control system and the system is tested and analyzed. Simultaneously, to improve trajectory planning speeds, R control trajectory planning is used. Through improved algorithm design, a trajectory interpolation algorithm is established. The robot control system is based on R-dominated multi-objective trajectory planning. System stack function testing and system accuracy testing are conducted in a production environment. During palletizing function testing, the system’s single-step code packet time is stable at approximately 5.8 s and the average evolutionary algebra for each layer ranges between 32.49 and 45.66, which can save trajectory planning time. During system accuracy testing, the palletizing robot system’s repeated positioning accuracy is tested. The repeated positioning accuracy error is currently 10−1 mm and is mainly caused by friction and the machining process. By studying the control system of a four-degrees-of-freedom (4-DOF) palletizing robot based on the trajectory planning algorithm, the design predictions and effects are realized, thus providing a reference for more efficient future palletizing robot design. Although the working process still has some shortcomings, the research has major practical significance.

scholarly journals Collision-free path planning for welding manipulator via hybrid algorithm of deep reinforcement learning and inverse kinematics

2021 ◽  
Author(s):  
Jie Zhong ◽  
Tao Wang ◽  
Lianglun Cheng
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Free Path ◽  
Inverse Kinematics ◽  
Multiple Dimensions ◽  
Continuous State ◽  
Planning Algorithm ◽  
Convergence Performance ◽  
Path Planner ◽  
Action Spaces

AbstractIn actual welding scenarios, an effective path planner is needed to find a collision-free path in the configuration space for the welding manipulator with obstacles around. However, as a state-of-the-art method, the sampling-based planner only satisfies the probability completeness and its computational complexity is sensitive with state dimension. In this paper, we propose a path planner for welding manipulators based on deep reinforcement learning for solving path planning problems in high-dimensional continuous state and action spaces. Compared with the sampling-based method, it is more robust and is less sensitive with state dimension. In detail, to improve the learning efficiency, we introduce the inverse kinematics module to provide prior knowledge while a gain module is also designed to avoid the local optimal policy, we integrate them into the training algorithm. To evaluate our proposed planning algorithm in multiple dimensions, we conducted multiple sets of path planning experiments for welding manipulators. The results show that our method not only improves the convergence performance but also is superior in terms of optimality and robustness of planning compared with most other planning algorithms.

STAND-UP MOTION SUPPORT BY A MOBILE MANIPULATOR SYSTEM WITH HIGH SPEED TACTILE SENSORS

2011 ◽  
Vol 08 (03) ◽  
pp. 181-195
Author(s):  
ZHAOXIAN XIE ◽  
HISASHI YAMAGUCHI ◽  
MASAHITO TSUKANO ◽  
AIGUO MING ◽  
MAKOTO SHIMOJO
Keyword(s):  
Fuzzy Logic ◽  
Feedback Control ◽  
Experimental Verification ◽  
High Speed ◽  
Center Of Pressure ◽  
Tactile Sensor ◽  
Mobile Manipulator ◽  
Tactile Sensing ◽  
Robot Arm ◽  
Tactile Sensors

As one of the home services by a mobile manipulator system, we are aiming at the realization of the stand-up motion support for elderly people. This work is charaterized by the use of real-time feedback control based on the information from high speed tactile sensors for detecting the contact force as well as its center of pressure between the assisted human and the robot arm. First, this paper introduces the design of the tactile sensor as well as initial experimental results to show the feasibility of the proposed system. Moreover, several fundamental tactile sensing-based motion controllers necessary for the stand-up motion support and their experimental verification are presented. Finally, an assist trajectory generation method for the stand-up motion support by integrating fuzzy logic with tactile sensing is proposed and demonstrated experimentally.

Robot Trajectory Planning Using Rational Frenet-Serret Curves

Volume 2 ◽  
2004 ◽  
Author(s):  
Reza Ravani ◽  
Ali Meghdari
Keyword(s):  
Trajectory Planning ◽  
Computer Animation ◽  
Rational Curves ◽  
Robot Arm ◽  
Robot Trajectory ◽  
Arm Motion ◽  
Sweep Surface ◽  
And Robotics ◽  
Rotation Minimizing Frame ◽  
Robot Trajectory Planning

The aim of this paper is to demonstrate that the techniques of Computer Aided Geometric Design such as spatial rational curves and surfaces could be applied to Kinematics, Computer Animation and Robotics. For this purpose we represent a method which utilizes a special class of rational curves called Rational Frenet-Serret (RF) [8] curves for robot trajectory planning. RF curves distinguished by the property that the motion of their Frenet-Serret frame is rational. We describe an algorithm for interpolation of positions by a rational Frenet-Serret motion. Further more we provide an analysis on spatial frames (Frenet-Serret frame and Rotation Minimizing frame) for smooth robot arm motion and investigate their applications in sweep surface modeling.

Sign in / Sign up

Export Citation Format

Share Document