scholarly journals Multisensor-Based Autonomous Grasp Planning for Mobile Manipulator Navigation System with a Novel Soft Gripper

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Heng Zhang ◽  
Yingbai Hu ◽  
Jianghua Duan ◽  
Qing Gao ◽  
Langcheng Huo ◽  
...  
Keyword(s):  
High Performance ◽  
Visual Recognition ◽  
Vision System ◽  
Recognition Algorithm ◽  
Mobile Manipulator ◽  
Mobile Manipulators ◽  
Success Rates ◽  
Complex Environments ◽  
Grasp Planning ◽  
Window Approach

Mobile manipulators are widely used in different fields for transferring and grasping tasks such as in medical assisting devices, industrial production, and hotel services. It is challenging to improve navigation accuracies and grasping success rates in complex environments. In this paper, we develop a multisensor-based mobile grasping system which is configured with a vision system and a novel gripper set in an UR5 manipulator. Additionally, an error term of a cost function based on DWA (dynamic window approach) is proposed to improve the navigation performance of the mobile platform through visual guidance. In the process of mobile grasping, the size and position of the object can be identified by a visual recognition algorithm, and then the finger space and chassis position can be automatically adjusted; thus, the object can be grasped by the UR5 manipulator and gripper. To demonstrate the proposed methods, comparison experiments are also conducted using our developed mobile grasping system. According to the analysis of the experimental results, the motion accuracy of the mobile chassis has been improved significantly, satisfying the requirements of navigation and grasping success rates, as well as achieving a high performance over a wide grasping size range from 1.7 mm to 200 mm.

Trajectory planning of mobile manipulators using dynamic programming approach

Robotica ◽  
2012 ◽  
Vol 31 (4) ◽  
pp. 643-656 ◽  
Author(s):  
M. H. Korayem ◽  
M. Irani ◽  
A. Charesaz ◽  
A. H. Korayem ◽  
A. Hashemi
Keyword(s):  
Dynamic Programming ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Vision System ◽  
Optimal Path ◽  
Optimization Method ◽  
Mobile Manipulator ◽  
Programming Approach ◽  
Planning Problem ◽  
Mobile Manipulators

SUMMARYThis paper presents a solution for optimal trajectory planning problem of robotic manipulators with complicated dynamic equations. The main goal is to find the optimal path with maximum dynamic load carrying capacity (DLCC). Proposed method can be implemented to problems of both motion along a specified path and point-to-point motion. Dynamic Programming (DP) approach is applied to solve optimization problem and find the positions and velocities that minimize a pre-defined performance index. Unlike previous attempts, proposed method increases the speed of convergence by using the sequential quadratic programming (SQP) formulation. This formulation is used for solving problems with nonlinear constraints. Also, this paper proposes a new algorithm to design optimal trajectory with maximum DLCC for both fixed and mobile base mechanical manipulators. Algorithms for DLCC calculations in previous works were based on indirect optimization method or linear programming approach. The proposed trajectory planning method is applied to a linear tracked Puma and the mobile manipulator named Scout. Application of this algorithm is confirmed and simulation results are compared with experimental results for Scout robot. In experimental test, results are obtained using a new stereo vision system to determine the position of the robot end-effector.

scholarly journals Mobile manipulator control through gesture recognition using IMUs and Online Lazy Neighborhood Graph search

ACTA IMEKO ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 3 ◽  
Author(s):  
Padmaja Vivek Kulkarni ◽  
Boris Illing ◽  
Bastian Gaspers ◽  
Bernd Brüggemann ◽  
Dirk Schulz
Keyword(s):  
Gesture Recognition ◽  
False Positive Rate ◽  
Recognition Algorithm ◽  
Mobile Manipulator ◽  
Success Rates ◽  
Neighborhood Graph ◽  
Arm Motions ◽  
Training Samples ◽  
Positive Rate ◽  
Measurement Units

Gesture-based control potentially eliminates the need for wearisome physical controls and facilitates easy interaction between a human and a robot. At the same time, it is intuitive and enables a natural means of control. In this paper, we present and evaluate a framework for gesture recognition using four wearable Inertial Measurement Units (IMUs) to indirectly control a mobile robot. Six gestures involving different hand and arm motions are defined. A novel algorithm based on an Online Lazy Neighborhood Graph (OLNG) search is used to recognise and classify the gestures online. A software framework is developed to control a robotic platform through integrating our gesture recognition algorithm with a Robot Operating System (ROS), which is in turn used to trigger predefined robot behaviours. Experiments show that the framework is able to correctly detect and classify six different gestures in real time with average success rates of 81.61 % and 81.67 %, while keeping the false-positive rate low by designing and using only 126 training samples.

Research on the Visual Recognition Algorithm for Loading Robot Vision System

2012 ◽  
Vol 271-272 ◽  
pp. 1645-1648
Author(s):  
Yong Tao Yang ◽  
Huai Xing Wen
Keyword(s):  
Approximation Algorithm ◽  
Stereo Vision ◽  
Visual Recognition ◽  
Object Segmentation ◽  
Vision System ◽  
Robot Vision ◽  
Target Object ◽  
Recognition Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

In order to study the questions about the recognition of relative position for the operating object and calculation of the object volume in the loading robot binocular stereo vision system. Based on the characteristics of the operating object, proposed the method that use of its vertices only to match the corresponding point of the camera imaging for location identification, also raised the approximation algorithm that firstly, cut up the whole, followed by calculate the volume of the various parts, then carry out the sum of the each segmentation volume. Experiments and analysis showed that the distance of camera and the object greater affect the visual system, less impact on the intensity of light；In the target object segmentation， the number of partition k=11 is better. Both methods produced the small errors for the visual recognition of the system, it can meet actual needs.

SVM-based global vision system of sports competition and action recognition

2020 ◽  
pp. 1-12
Author(s):  
Changxin Sun ◽  
Di Ma
Keyword(s):  
Target Recognition ◽  
Vision System ◽  
Task Assignment ◽  
Recognition Algorithm ◽  
Control Factor ◽  
Training Time ◽  
Adaboost Algorithm ◽  
Advantages And Disadvantages ◽  
Time Control ◽  
Correlation Degree

In the research of intelligent sports vision systems, the stability and accuracy of vision system target recognition, the reasonable effectiveness of task assignment, and the advantages and disadvantages of path planning are the key factors for the vision system to successfully perform tasks. Aiming at the problem of target recognition errors caused by uneven brightness and mutations in sports competition, a dynamic template mechanism is proposed. In the target recognition algorithm, the correlation degree of data feature changes is fully considered, and the time control factor is introduced when using SVM for classification,At the same time, this study uses an unsupervised clustering method to design a classification strategy to achieve rapid target discrimination when the environmental brightness changes, which improves the accuracy of recognition. In addition, the Adaboost algorithm is selected as the machine learning method, and the algorithm is optimized from the aspects of fast feature selection and double threshold decision, which effectively improves the training time of the classifier. Finally, for complex human poses and partially occluded human targets, this paper proposes to express the entire human body through multiple parts. The experimental results show that this method can be used to detect sports players with multiple poses and partial occlusions in complex backgrounds and provides an effective technical means for detecting sports competition action characteristics in complex backgrounds.

Sitsen: Passive sitting posture sensing based on wireless devices

2021 ◽  
Vol 17 (7) ◽  
pp. 155014772110248
Author(s):  
Miaoyu Li ◽  
Zhuohan Jiang ◽  
Yutong Liu ◽  
Shuheng Chen ◽  
Marcin Wozniak ◽  
...  
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
High Performance ◽  
Learning Algorithm ◽  
Low Cost ◽  
Recognition System ◽  
Sitting Posture ◽  
Average Accuracy ◽  
Phase Variations ◽  
Window Approach

Physical health diseases caused by wrong sitting postures are becoming increasingly serious and widespread, especially for sedentary students and workers. Existing video-based approaches and sensor-based approaches can achieve high accuracy, while they have limitations like breaching privacy and relying on specific sensor devices. In this work, we propose Sitsen, a non-contact wireless-based sitting posture recognition system, just using radio frequency signals alone, which neither compromises the privacy nor requires using various specific sensors. We demonstrate that Sitsen can successfully recognize five habitual sitting postures with just one lightweight and low-cost radio frequency identification tag. The intuition is that different postures induce different phase variations. Due to the received phase readings are corrupted by the environmental noise and hardware imperfection, we employ series of signal processing schemes to obtain clean phase readings. Using the sliding window approach to extract effective features of the measured phase sequences and employing an appropriate machine learning algorithm, Sitsen can achieve robust and high performance. Extensive experiments are conducted in an office with 10 volunteers. The result shows that our system can recognize different sitting postures with an average accuracy of 97.02%.

scholarly journals UAV Recognition Based on Micro-Doppler Dynamic Attribute-Guided Augmentation Algorithm

2021 ◽  
Vol 13 (6) ◽  
pp. 1205
Author(s):  
Caidan Zhao ◽  
Gege Luo ◽  
Yilin Wang ◽  
Caiyun Chen ◽  
Zhiqiang Wu
Keyword(s):  
Recognition Performance ◽  
Principal Component ◽  
Texture Features ◽  
Training Model ◽  
Recognition Algorithm ◽  
Discrete Wavelet ◽  
Dynamic Feature ◽  
Complex Environments ◽  
Time Frequency ◽  
Model Training

A micro-Doppler signature (m-DS) based on the rotation of drone blades is an effective way to detect and identify small drones. Deep-learning-based recognition algorithms can achieve higher recognition performance, but they needs a large amount of sample data to train models. In addition to the hovering state, the signal samples of small unmanned aerial vehicles (UAVs) should also include flight dynamics, such as vertical, pitch, forward and backward, roll, lateral, and yaw. However, it is difficult to collect all dynamic UAV signal samples under actual flight conditions, and these dynamic flight characteristics will lead to the deviation of the original features, thus affecting the performance of the recognizer. In this paper, we propose a small UAV m-DS recognition algorithm based on dynamic feature enhancement. We extract the combined principal component analysis and discrete wavelet transform (PCA-DWT) time–frequency characteristics and texture features of the UAV’s micro-Doppler signal and use a dynamic attribute-guided augmentation (DAGA) algorithm to expand the feature domain for model training to achieve an adaptive, accurate, and efficient multiclass recognition model in complex environments. After the training model is stable, the average recognition accuracy rate can reach 98% during dynamic flight.

Cooperation and Null-Space Control of Networked Omni-Directional Mobile Manipulators

2020 ◽  
Author(s):  
Michael John Chua ◽  
Yen-Chen Liu
Keyword(s):  
Degrees Of Freedom ◽  
Null Space ◽  
Kinematic Model ◽  
Mobile Manipulator ◽  
Main Task ◽  
Mobile Manipulators ◽  
Robot Arm ◽  
Task Space ◽  
End Effector ◽  
Mobile Base

Abstract This paper presents cooperation and null-space control for networked mobile manipulators with high degrees of freedom (DOFs). First, kinematic model and Euler-Lagrange dynamic model of the mobile manipulator, which has an articulated robot arm mounted on a mobile base with omni-directional wheels, have been presented. Then, the dynamic decoupling has been considered so that the task-space and the null-space can be controlled separately to accomplish different missions. The motion of the end-effector is controlled in the task-space, and the force control is implemented to make sure the cooperation of the mobile manipulators, as well as the transportation tasks. Also, the null-space control for the manipulator has been combined into the decoupling control. For the mobile base, it is controlled in the null-space to track the velocity of the end-effector, avoid other agents, avoid the obstacles, and move in a defined range based on the length of the manipulator without affecting the main task. Numerical simulations have been addressed to demonstrate the proposed methods.

scholarly journals On path following control of nonholonomic mobile manipulators

2009 ◽  
Vol 19 (4) ◽  
pp. 561-574 ◽  
Author(s):  
Alicja Mazur ◽  
Dawid Szakiel
Keyword(s):  
Control Algorithm ◽  
Dynamic Control ◽  
Path Following ◽  
Mobile Manipulator ◽  
Mobile Manipulators ◽  
Control Laws ◽  
Kinematic Control ◽  
Motion Constraints ◽  
Path Following Control ◽  
Cascade Structure

On path following control of nonholonomic mobile manipulatorsThis paper describes the problem of designing control laws for path following robots, including two types of nonholonomic mobile manipulators. Due to a cascade structure of the motion equation, a backstepping procedure is used to achieve motion along a desired path. The control algorithm consists of two simultaneously working controllers: the kinematic controller, solving motion constraints, and the dynamic controller, preserving an appropriate coordination between both subsystems of a mobile manipulator, i.e. the mobile platform and the manipulating arm. A description of the nonholonomic subsystem relative to the desired path using the Frenet parametrization is the basis for formulating the path following problem and designing a kinematic control algorithm. In turn, the dynamic control algorithm is a modification of a passivity-based controller. Theoretical deliberations are illustrated with simulations.

scholarly journals 3D Reconstruction of Pedestrian Trajectory with Moving Direction Learning and Optimal Gait Recognition

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Binbin Wang ◽  
Tingli Su ◽  
Xuebo Jin ◽  
Jianlei Kong ◽  
Yuting Bai
Keyword(s):  
Learning Algorithm ◽  
Gait Recognition ◽  
Vertical Direction ◽  
Recognition Algorithm ◽  
Measurement Unit ◽  
Complex Environments ◽  
Position Change ◽  
Vertical Movements ◽  
Moving Direction ◽  
Optimal Gait

An inertial measurement unit-based pedestrian navigation system that relies on the intelligent learning algorithm is useful for various applications, especially under some severe conditions, such as the tracking of firefighters and miners. Due to the complexity of the indoor environment, signal occlusion problems could lead to the failure of certain positioning methods. In complex environments, such as those involving fire rescue and emergency rescue, the barometric altimeter fails because of the influence of air pressure and temperature. This paper used an optimal gait recognition algorithm to improve the accuracy of gait detection. Then a learning-based moving direction determination method was proposed. With the Kalman filter and a zero-velocity update algorithm, different gaits could be accurately recognized, such as going upstairs, downstairs, and walking flat. According to the recognition results, the position change in the vertical direction could be reasonably corrected. The obtained 3D trajectory involving both horizontal and vertical movements has shown that the accuracy is significantly improved in practical complex environments.

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