scholarly journals Collision-Free Motion Planning of a Six-Link Manipulator Used in a Citrus Picking Robot

2021 ◽  
Vol 11 (23) ◽  
pp. 11336
Author(s):  
Zuoliang Tang ◽  
Lijia Xu ◽  
Yuchao Wang ◽  
Zhiliang Kang ◽  
Hong Xie

This paper presents the results of a motion planning algorithm that has been used in an intelligent citrus-picking robot consisting of a six-link manipulator. The real-time performance of a motion planning algorithm is urgently required by the picking robot. Within the artificial potential field (APF) method, the motion planning of the picking manipulator was basically solved. However, the real-time requirement of the picking robot had not been totally satisfied by APF because of some native defects, such as the large number of calculations used to map forces into torques by the Jacobian matrix, local minimum trap, and target not reachable problem, which greatly reduce motion planning efficiency and real-time performance of citrus-picking robots. To circumvent those problems, this paper proposed some novel methods that improved the mathematical models of APF and directly calculates the attractive torques in the joint space. By using the latter approach, the calculation time and the total joint error were separately reduced by 54.89% and 45.41% compared with APF. Finally, the novel algorithm is presented and demonstrated with some illustrative examples of the citrus picking robot, both offline during the design phase as well as online during a realistic picking test.

2020 ◽  
Vol 10 (21) ◽  
pp. 7716
Author(s):  
Tamás Hegedűs ◽  
Balázs Németh ◽  
Péter Gáspár

In the development of autonomous vehicles, the design of real-time motion-planning is a crucial problem. The computation of the vehicle trajectory requires the consideration of safety, dynamic and comfort aspects. Moreover, the prediction of the vehicle motion in the surroundings and the real-time planning of the autonomous vehicle trajectory can be complex tasks. The goal of this paper is to present low-complexity motion-planning for overtaking scenarios in parallel traffic. The developed method is based on the generation of a graph, which contains feasible vehicle trajectories. The reduction of the complexity in the real-time computation is achieved through the reduction of the graph with clustering. In the motion-planning algorithm, the predicted motion of the surrounding vehicles is taken into consideration. The prediction algorithm is based on density functions of the surrounding vehicle motion, which are developed through real measurements. The resulted motion-planning algorithm is able to guarantee a safe and comfortable trajectory for the autonomous vehicle. The effectiveness of the method is illustrated through simulation examples using a high-fidelity vehicle dynamic simulator.


2021 ◽  
Vol 40 (3) ◽  
pp. 1-12
Author(s):  
Hao Zhang ◽  
Yuxiao Zhou ◽  
Yifei Tian ◽  
Jun-Hai Yong ◽  
Feng Xu

Reconstructing hand-object interactions is a challenging task due to strong occlusions and complex motions. This article proposes a real-time system that uses a single depth stream to simultaneously reconstruct hand poses, object shape, and rigid/non-rigid motions. To achieve this, we first train a joint learning network to segment the hand and object in a depth image, and to predict the 3D keypoints of the hand. With most layers shared by the two tasks, computation cost is saved for the real-time performance. A hybrid dataset is constructed here to train the network with real data (to learn real-world distributions) and synthetic data (to cover variations of objects, motions, and viewpoints). Next, the depth of the two targets and the keypoints are used in a uniform optimization to reconstruct the interacting motions. Benefitting from a novel tangential contact constraint, the system not only solves the remaining ambiguities but also keeps the real-time performance. Experiments show that our system handles different hand and object shapes, various interactive motions, and moving cameras.


2014 ◽  
Vol 933 ◽  
pp. 584-589
Author(s):  
Zhi Chun Zhang ◽  
Song Wei Li ◽  
Wei Ren Wang ◽  
Wei Zhang ◽  
Li Jun Qi

This paper presents a system in which the cluster devices are controlled by single-chip microcomputers, with emphasis on the cluster management techniques of single-chip microcomputers. Each device in a cluster is controlled by a single-chip microcomputer collecting sample data sent to and driving the device by driving data received from the same cluster management computer through COMs. The cluster management system running on the cluster management computer carries out such control as initial SCM identification, run time slice management, communication resource utilization, fault tolerance and error corrections on single-chip microcomputers. Initial SCM identification is achieved by signal responses between the single-chip microcomputers and the cluster management computer. By using the port priority and the parallelization of serial communications, the systems real-time performance is maximized. The real-time performance can be adjusted and improved by increasing or decreasing COMs and the ports linked to each COM, and the real-time performance can also be raised by configuring more cluster management computers. Fault-tolerant control occurs in the initialization phase and the operational phase. In the initialization phase, the cluster management system incorporates unidentified single-chip microcomputers into the system based on the history information recorded on external storage media. In the operational phase, if an operation error of reading and writing on a single-chip microcomputer reaches a predetermined threshold, the single-chip microcomputer is regarded as serious fault or not existing. The cluster management system maintains accuracy maintenance database on external storage medium to solve nonlinear control of specific devices and accuracy maintenance due to wear. The cluster management system uses object-oriented method to design a unified driving framework in order to enable the implementation of the cluster management system simplified, standardized and easy to transplant. The system has been applied in a large-scale simulation system of 230 single-chip microcomputers, which proves that the system is reliable, real-time and easy to maintain.


Author(s):  
Junyi Hou ◽  
Lei Yu ◽  
Yifan Fang ◽  
Shumin Fei

Aiming at the problem that the mixed noise interference caused by the mixed projection noise system is not accurate and the real-time performance is poor, this article proposes an adaptive system switching filtering method based on Bayesian estimation switching rules. The method chooses joint bilateral filtering and improved adaptive median filtering as the filtering subsystems and selects the sub-filtering system suitable for the noise by switching rules to achieve the purpose of effectively removing noise. The simulation experiment was carried out by the self-developed human–computer interactive projection image system platform. Through the subjective evaluation, objective evaluation, and running time comparison analysis, a better filtering effect was achieved, and the balance between the filtering precision and the real-time performance of the interactive system was well obtained. Therefore, the proposed method can be widely applied to various human–computer interactive image filtering systems.


2016 ◽  
Vol 4 (3) ◽  
pp. 163-181
Author(s):  
Pouria Sarhadi ◽  
Reza Nad Ali Niachari ◽  
Morteza Pouyan Rad ◽  
Javad Enayati

Purpose The purpose of this paper is to propose a software engineering procedure for real-time software development and verification of an autonomous underwater robotic system. High performance and robust software are one of the requirements of autonomous systems design. A simple error in the software can easily lead to a catastrophic failure in a complex system. Then, a systematic procedure is presented for this purpose. Design/methodology/approach This paper utilizes software engineering tools and hardware-inthe-loop (HIL) simulations for real-time system design of an autonomous underwater robot. Findings In this paper, the architecture of the system is extracted. Then, using software engineering techniques a suitable structure for control software is presented. Considering the desirable targets of the robot, suitable algorithms and functions are developed. After the development stage, proving the real-time performance of the software is disclosed. Originality/value A suitable approach for analyzing the real-time performance is presented. This approach is implemented using HIL simulations. The developed structure is applicable to other autonomous systems.


2016 ◽  
Vol 40 (3) ◽  
pp. 383-397 ◽  
Author(s):  
Bahman Nouri Rahmat Abadi ◽  
Sajjad Taghvaei ◽  
Ramin Vatankhah

In this paper, an optimal motion planning algorithm and dynamic modeling of a planar kinematically redundant manipulator are considered. Kinematics of the manipulator is studied, Jacobian matrix is obtained and the dynamic equations are derived using D’Alembert’s principle. Also, a novel actuation method is introduced and applied to the 3-PRPR planar redundant manipulator. In this approach, the velocity of actuators is determined in such a way to minimize the 2-norm of the velocity vector, subjected to the derived kinematic relations as constraints. Having the optimal motion planning, the motion is controlled via a feedback linearization controller. The motion of the manipulator is simulated and the effectiveness of the proposed actuation strategy and the designed controller is investigated.


Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1077 ◽  
Author(s):  
Guoxing Bai ◽  
Yu Meng ◽  
Li Liu ◽  
Weidong Luo ◽  
Qing Gu ◽  
...  

Recently, model predictive control (MPC) is increasingly applied to path tracking of mobile devices, such as mobile robots. The characteristics of these MPC-based controllers are not identical due to the different approaches taken during design. According to the differences in the prediction models, we believe that the existing MPC-based path tracking controllers can be divided into four categories. We named them linear model predictive control (LMPC), linear error model predictive control (LEMPC), nonlinear model predictive control (NMPC), and nonlinear error model predictive control (NEMPC). Subsequently, we built these four controllers for the same mobile robot and compared them. By comparison, we got some conclusions. The real-time performance of LMPC and LEMPC is good, but they are less robust to reference paths and positioning errors. NMPC performs well when the reference velocity is high and the radius of the reference path is small. It is also robust to positioning errors. However, the real-time performance of NMPC is slightly worse. NEMPC has many disadvantages. Like LMPC and LEMPC, it performs poorly when the reference velocity is high and the radius of the reference path is small. Its real-time performance is also not good enough.


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