iiwa_krc4 Object Detection Dataset and Pre-Trained Model by yolo training

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Explore Dataset

Here are a few use cases for this project:

Industrial Automation: This model can be used for identifying, monitoring, and controlling different parts of a KUKA iiwa robot. This includes tracking the status of the control pendant, the locking mechanism, and the overall robot, supporting real-time optimization of industrial automation processes.
Robotics Research & Education: Using the 'iiwa_krc4' model, students and researchers can gain a better understanding of different classes of iiwa robots and their components. This application can be particularly helpful in robotics lab sessions, where learners need to visually identify and differentiate the components and operations, such as unlocking or activating the robot controller.
Inspection & Maintenance: This model can be used to develop systems for remote or automatic inspection and maintenance of iiwa robots. For example, it could detect when locks are engaged or not, or if the teach pendant (used for programming and controlling the robots) is in place or not, thereby improving servicing efficiency.
Assembly Line Optimization: The model can help optimize assembly line operations by visually tracking and identifying if the iiwa robot is active, if the robot controller is functioning well, or if the teach pendant is being utilized effectively.
Advanced Manufacturing Training Simulations: This model can be used to create training simulations for new employees in advanced manufacturing settings. Trainees can learn how to identify iiwa robots and their components and understand their operations, such as how to lock/unlock the robot and use the teach pendant and robot controller.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            iiwa_krc4_dataset,
                            title = { iiwa_krc4 Dataset },
                            type = { Open Source Dataset },
                            author = { yolo training },
                            howpublished = { \url{ https://universe.roboflow.com/yolo-training-dwcmd/iiwa_krc4 } },
                            url = { https://universe.roboflow.com/yolo-training-dwcmd/iiwa_krc4 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-05-15 },
                            }