Development Service of Systemic Control Algorithm for Development of Safety Guidelines for Mobile Cooperative Robot Workshop
Goal of This Project
Although it is a safe enough cooperative robot, there is no difference from the function of a fixed cooperative robot because the cooperative robot attached to the mobile robot cannot be operated while on the move. Therefore, there is a problem that the efficiency of use is significantly reduced by applying the same regulations as industrial robots for work during the installation and movement of the robot.
Although mobile cooperative robots must perform tasks on the move, such as transportation between processes and intermediate work, collaboration between workers and mobile cooperative robots in logistics warehouses, and collaboration of many cooperative robots, existing regulations prohibit the operation of these robots.
The purpose is to increase the utilization of robots through the development of a whole-body control algorithm for mobile cooperative robots and to improve work efficiency when operating in the workplace
In addition, implementing a simulator with a control algorithm, it is intended to be used to analyze risk factors between workers and robots and to review the work efficiency of mobile cooperative robots when developing workplace safety guidelines for mobile cooperative robots.
Project Contents
Development of Mechanical Models for Mobile Cooperative Robots
Conducting mechanical modeling of the mobile cooperative-provided robots
Verification of results of mechanical modeling through simulation
When developing a mechanical model, an integrated mechanical model was developed based on instrumental information of cooperative robots and mobile robots (6 degrees of freedom cooperative robots, 3 degrees of freedom mobile robots).
Additional mathematical modeling was included when Jacobian or inverse mechanical analysis was required in the development of the Whole Body control algorithm
Development of Whole-body Control Algorithm for Mobile Cooperative Robots
Development of a location-based Whole Body control algorithm model.
Deriving Control Inputs for Whole Body Control of Mobile and Cooperative Robots.
Development of a Foldbody Control Algorithm Considering Singularity in the Work Area.
Implementation of a Mobile Cooperative Robot Simulator with Whole-body Control Algorithm
Apply the whole-body control algorithm of the mobile cooperative robot to the simulator provided (Simulator provided after contract)
Development of 2 examples of applying the whole-body control algorithm
Following sine wave
Keeping the distal end at the same point
Hyundai Mobis Mobile Manipulator Whole-Body Control
Goal of This Project
This project is about compliance control of a mobile manipulator that integrates a mobile robot equipped with 4-wheel independent steering and vertical lift with a UR5e manipulator. Each lift can move independently, allowing for the adjustment of the mobile robot's body tilt and height. The main goal of this project is to minimize the impact of collisions with the environment through whole-body admittance control.
Project Contents
Whole-body control of mobile manipulator for dynamic stability implementation
Corner module-based mobile manipulator (manipulator 6 degrees of freedom , mobile 12 degrees of freedom)
Whole body optimal control framework using the redundancy of mobile manipulator to perform multitasks
Control to mitigate impact in case of contact with environment
Task configuration techniques for implementing Environment adaptability
Task priority determination algorithms that change the robot’s task priorities according to human willingness to work or changes in the environment
Implementation and Test Evaluation of Algorithms for Mobile Manipulators
Goal of This Project
This project aims to control a dual-arm robot that shares a workspace in a confined area, ensuring that the two arms do not collide with each other while efficiently performing their respective tasks.
Project Contents
Hybrid planner
Development of local planner using Nonlinear Model Predictive Controller
Using Trajopt algorithm as global planner
Combining global and local planners to implement hybrid planners that can be applied to dual-arm robots
Employing a Control Barrier Function to Prevent Collisions with the Opposite UR20
Dual-arm control using hybrid planner
The robot's left arm was designated as the main arm and the right arm as the sub-arm. To test effective collision avoidance, global planning was applied to the left arm, while hybrid planning was applied to the right arm. The results showed that the right arm successfully avoided the left arm and conducted the task