Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics
Abstract
:1. Introduction
- An ever-increasing customization of products and short lifecycle, which require an increase in the flexibility of the production means (one unique system must handle all of the product diversity and operations) [2,3]. Robots fit perfect into this topic due to their versatility; robot programs can adapt to the customizations of the products.
- A large variation in production volumes, which requires an increase in the reconfigurability of production (one system for one product/task within recombinable production lines) [2,4]. Robotic mobile platforms play an important role in this trend; easy to move robots are necessary in some production chains where production volumes change frequently.
- Limited access to skilled operators due to an aging workforce, changes in education and an ever-faster technology development. This requires new solutions to assist operators and provide collaborative work environments [5]. Collaborative robotics are being developed for this topic.
2. Materials and Methods
2.1. State Machine-Based Execution Coordination for Dual-Arm Robots
2.1.1. Proposed Architecture
2.1.2. Core Description
2.1.3. Description of the Developed States
2.2. Flexible Application Development
2.2.1. Software Structure of the Framework
2.2.2. Execution Engine
2.2.3. Application to Executable XML
3. Results
3.1. Validation in a Real Use Case
3.2. Evaluation
4. Discussion
5. Conclusions and Future Work
Acknowledgments
Author Contributions
Conflicts of Interest
References
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State | Description |
---|---|
Ready | The state machine is ready for receiving new instructions. This state is waiting until the execution engine sends a new request. |
Cartesian articular motion | Manages the robot movements both in the Cartesian space and the articular space. If the movement cannot be executed correctly, there is an error handling state to manage it. |
Full body coordinated motion | Allows controlling both arms in coordination. Two arms must be in this state to start coordinated motion. Sending the values of the 15 joints of the robot is necessary. |
Record trajectory | Allows recording trajectories with a trajectory planner or teaching by demonstration. These trajectories are stored in a database for future use. |
Trajectory execution | Executes trajectories, provided by a trajectory planner or previously stored in a database. |
End-effector operation | Manages end-effector operations; depending on the end effector, different operations can be made, e.g., gripper open/close, deburring tool activate/deactivate, screwing operation, etc. |
Vision operation | Manages different computer vision operations. This includes picture acquisition, processing and reference frame transformation, among others. As the robotic system has multiple vision systems, this state is responsible for managing them depending on the operation that will be executed. |
Master/slave mode | Puts robot in bi-manual coordinated manipulation mode; one arm actuates as the master and the other one as the slave. Consists of planning a trajectory for the master arm and then computing this trajectory with an offset for the slave arm. |
State | Signal | Transition to |
---|---|---|
Ready | motion_request | Cartesian/articular motion |
vision_request | Vision operation | |
end_effector_request | End effector operation | |
... | ... | |
end | Finish | |
Cartesian | ok | Ready |
Articular | pause | Pause |
motion | stop | Stop |
error | Error handling | |
Pause | resume | Cartesian/articular motion |
stop | Stop | |
error | Error handling | |
Stop | error | Error handling |
Error | ok | Ready |
handling | end | Finish |
Quality | Online Programming | Offline Programming | State Machine and Skill Based Programming Framework |
---|---|---|---|
Ease of use | − | + | ++ |
Adaptability | − | + | ++ |
Reliability | − | +− | + |
Subsetability | − | + | ++ |
Performance | ++ | ++ | − |
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Herrero, H.; Outón, J.L.; Puerto, M.; Sallé, D.; López de Ipiña, K. Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics. Sensors 2017, 17, 1249. https://doi.org/10.3390/s17061249
Herrero H, Outón JL, Puerto M, Sallé D, López de Ipiña K. Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics. Sensors. 2017; 17(6):1249. https://doi.org/10.3390/s17061249
Chicago/Turabian StyleHerrero, Héctor, Jose Luis Outón, Mildred Puerto, Damien Sallé, and Karmele López de Ipiña. 2017. "Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics" Sensors 17, no. 6: 1249. https://doi.org/10.3390/s17061249