Erratum to: Introduction of a unified robot intergration package

Humanoids playing soccer are required to solve a great variety of tasks: from perception to body motion, from decision making to team coordination. On the other hand, results from this community are sometimes underestimated or unexploited because of the dedicated software developed. In particular simulators are often designed for a specific robotics platform or in some other cases the integration with existing software and frameworks is hard to implement and time consuming. In this paper we introduce a novel virtual model to simulate the humanoid robot Aldebaran NAO. The URDF (Unified Robot Description Format) standard has been followed in order to maintain the model as general purpose as possible. Related plug-ins to make it works in Gazebo and V-REP simulation environments were also developed in order to test the model under ROS (Robot Operating System), a very common robotics framework.

The kinematic parameters of camera robot are described by Unified Robot Description Format (URDF). Compared to Denavit-Hartenberg (DH) method, URDF is more flexible. But DH method has an advantage in inverse solution control at position level. Sometimes only URDF file can be obtained due to the engineering project requirements, such as modularity and security. It is easy to convert DH to URDF. There is a lack of research for inverse conversion. In this paper, three conversion principles were proposed. The relationship of base coordinate system and joint coordinate system was divided into six situations. The DH transformation parameters were solved based on the three principles. Finally the extend conversion algorithm for serial joints chain was supplied. The robot kinematic conversion algorithm from URDF to DH provides a mathematical tool for requirements of engineering projects.

As we all know, the kinematic model of a robotic arm holds significant importance in the field of robotics. It can be utilized for applications such as path planning, trajectory generation, collision detection, and posture control. The commonly used kinematic modeling method in MATLAB is the Denavit-Hartenberg (DH) parameter method. However, this method has some drawbacks, such as its inability to handle singular postures and its unsuitability for continuous motion. In this study, we address the limitations of the DH parameter method by opting to create a Unified Robot Description Format (URDF) model file in MATLAB as an alternative to DH parameter-based modeling. By combining MATLAB simulation capabilities, we aim to achieve an analysis of kinematics. Additionally, we employ the MATLAB Toolbox to implement trajectory motion and control for the robotic arm. This approach aims to overcome challenges faced when dealing with redundant robotic arms, where DH parameter-based methods fail to obtain inverse kinematic solutions for the end effector and struggle with achieving continuous control.

The development of a three-axis delta robot, designed with servo motors for high-precision sorting tasks in pick-and-place operations, is presented in this paper. The system integrates at ailored Inverse Kinematics (IK) method and utilizes Model Predictive Control (MPC) to enhance motion control and trajectory accuracy. A comparative analysis of standard kinematics and the proposed IK model is conducted to evaluate improvements in precision. The robot is represented in the Robot Operating System (ROS) through a Unified Robot Description Format (URDF). MPC’s real-time testing underscores improved motion stability, diminished error rates, and appropriate ness for high-velocity industrial settings. The results underscore the promise of this delta robot design to fulfill the increasing demands for high-speed, high-precision sorting and handling tasks in contemporary manufacturing and logistics settings.

Building customized control system for specific robot is generally acknowledged as the fundamental section of developing auto robots. To simplify the programming process and increase the reuse of codes, this research develops a general method of developing customized robot simulation and control system software with robot operating system (ROS). First, a 3D visualization model is created in URDF (unified robot description format), and is viewed in Rviz to achieve motion planning with MoveIt! software package. Second, the machine vision provided by camera driver package in ROS enables the use of tools for image process, 3D point cloud analysis to reconstruct the environment to achieve accurate target location. Third, the communication protocols provided by ROS like serial, Modbus support the communication system development. To examine the method, we designed a tomato harvesting dual-arm robot, and conducted farming experiment with it. This work demonstrates the advantages of ROS when applied in robot control system development, and offers a plain method of building such system with ROS.

A comprehensive technique to plan path for a mobile robot with nonholonomic constraints through maze routing technique has been presented. Our robot uses a stereo vision based approach to detect the obstacles by creating dense 3D point clouds from the stereo images. ROS packages have been implemented on the robot for specific tasks of providing: i) Linear and angular velocity commands, ii) Calibration and rectification of the stereo images for generating point clouds, iii) Simulating the URDF (Unified Robot Description Format) module in real time, with respect to the real robot and iv) For visualizing the sensor data. For efficient path planning a hybrid technique using Lee's algorithm, modified by Hadlock and Soukup's algorithm has been implemented. Different path planning results have been shown using the maze routing algorithms. Preliminary results shows that Lee's algorithm is more time consuming in comparison with other algorithms. A hybrid of Lee's with Soukup's algorithm is more efficient but unpredictable for minimal path. A hybrid of Lee's with Hadlock's algorithm is the most efficient and least time consuming.

In this paper is presented an interfacing of a robotic arm with a motion planner and a 3D viewer (RViz). The main purpose of this work, is to manipulate and grip objects to transport them from one location to another using Robot Operating System (ROS). In order to do this task, a motion planner, who deal with constraints, i.e. collisions among the arm joints and objects, is used. Also a 3D viewer, called RViz, is used to visualize (online and offline) the motion of the arm. To easily interface the 3 degree of freedom (DOF) arm, it was designed using FreeCAD, as the output files used to print the arm, are simultaneously exported to create the Unified Robot Description Format (URDF) files required for the planner and viewer. A position-force controller for the gripper, previously presented, has been used to pick up and hold the object during the manipulation. Some experiments where carried out to asses the result of the interface, the execution of the motion planning avoiding collision and the grasp to the object. These results are shown and discussed.