Self-Sensing Feedback Control of a Bio-Inspired Robotic Shoulder with Two Degrees of Freedom

Core Concepts

This work presents a bio-inspired robotic shoulder with two degrees of freedom that utilizes self-sensing Peano-HASEL actuators, eliminating the need for external sensors and enabling precise closed-loop control of the end-effector position in the task space.

Abstract

The authors designed a bio-inspired robotic shoulder with two degrees of freedom (DoF) powered by antagonistic pairs of Peano-HASEL actuators. The key innovations of this work are:

Self-sensing capabilities: The HASEL actuators are equipped with a customized design that enables capacitive self-sensing of the actuator displacement, eliminating the need for external sensors.

Compact and compliant joint design: The ball-and-socket joint with a radius of 4 mm allows for a broad range of motion (over 80°) while maintaining a lightweight and compact system.

Tendon-based force transmission: The use of tendons for force transmission minimizes frictional losses and enables quick changes in movement while ensuring stable actuation at 3 Hz.

Closed-loop control: The authors implemented a PID controller that maps the reference and feedback signals between the task space and the tendon space, enabling precise control of the end-effector position without external sensors.

The authors conducted experiments to evaluate the performance of the self-sensing feedback control against a benchmark using a motion capture system. The results show that the self-sensing control achieved an RMSE of 4.245 mm for a lemniscate trajectory and 3.407 mm for a star-shaped trajectory, compared to the benchmark RMSEs of 2.869 mm and 2.798 mm, respectively.
The authors discuss the limitations of the current system, such as the torque limitations of the HASEL actuators, and suggest future research directions, including the integration of a third yaw axis, the use of advanced machine learning techniques for the estimation model, and the exploration of model-based control strategies.

Stats

The HASEL actuators used in the system can achieve a strain of up to 6.5% and a displacement of up to 8.6 mm under a 14 g load, and a strain of up to 5.8% and a displacement of up to 7.8 mm under a 34 g load.

Quotes

"The human shoulder stands out as an extraordinary biomechanical assembly, enabling complex movements to be carried out with precision and efficiency, thanks to its ball-and-socket joint, tendons, ligaments, and muscles."
"Drawing inspiration from the human shoulder, this work contributes a bio-inspired robotic shoulder with self-sensing control capabilities."

Key Insights Distilled From

Self-Sensing Feedback Control of an Electrohydraulic Robotic Shoulder

by Clemens C. C... at arxiv.org 04-08-2024

https://arxiv.org/pdf/2404.04079.pdf

Deeper Inquiries

How could the integration of additional sensors, such as force or torque sensors, further improve the performance and capabilities of the robotic shoulder

The integration of additional sensors, such as force or torque sensors, could significantly enhance the performance and capabilities of the robotic shoulder in several ways. Firstly, force sensors could provide real-time feedback on the forces exerted by the robotic shoulder during manipulation tasks. This information could be crucial for ensuring safe interactions with the environment and objects, preventing damage or injury. By incorporating force sensors, the robotic shoulder could adjust its force application based on the task requirements, leading to more precise and controlled movements.
Secondly, torque sensors could offer valuable insights into the torque levels experienced by the joints of the robotic shoulder. This data could help in optimizing the control algorithms to minimize energy consumption, reduce wear and tear on the actuators, and enhance overall efficiency. Additionally, torque sensors could enable the robotic shoulder to detect and respond to unexpected external forces, improving its adaptability and robustness in dynamic environments.
Furthermore, the integration of force and torque sensors could enable advanced functionalities such as impedance control, where the robotic shoulder can dynamically adjust its stiffness and compliance based on the task at hand. This capability would be particularly beneficial for tasks that require interaction with delicate objects or human collaborators, as the robotic shoulder could modulate its behavior to ensure safety and precision.
In conclusion, the incorporation of additional sensors like force and torque sensors would not only enhance the performance and capabilities of the robotic shoulder but also enable more sophisticated control strategies and functionalities, making the system more versatile and intelligent.

What are the potential challenges and limitations in scaling up this design to larger, more complex robotic systems with multiple degrees of freedom

Scaling up the design of the robotic shoulder to larger, more complex robotic systems with multiple degrees of freedom poses several potential challenges and limitations. One primary challenge is the increased complexity of the control algorithms required to coordinate and synchronize the movements of multiple actuators and joints. As the number of degrees of freedom increases, the computational demands and the complexity of the control architecture also escalate, making real-time control more challenging.
Another challenge is the mechanical design and integration of a larger system. As the size and complexity of the robotic system grow, issues related to structural integrity, weight distribution, and mechanical constraints become more pronounced. Ensuring the stability, durability, and safety of a larger robotic system with multiple degrees of freedom would require meticulous design considerations and thorough testing.
Moreover, the scalability of the self-sensing capabilities developed for the robotic shoulder to a larger system may present challenges in terms of sensor placement, data processing, and calibration. Ensuring accurate and reliable feedback from multiple sensors across a more extensive system would require sophisticated signal processing techniques and calibration procedures to maintain precision and consistency.
Despite these challenges, scaling up the design of the robotic shoulder to larger, more complex systems with multiple degrees of freedom offers exciting opportunities for creating advanced robotic platforms capable of performing intricate tasks with dexterity and efficiency. Overcoming the challenges through innovative design solutions, advanced control strategies, and robust testing methodologies would be essential for realizing the full potential of such systems.

How could the self-sensing and control strategies developed in this work be applied to other types of soft or compliant actuators to enable more versatile and adaptable robotic systems

The self-sensing and control strategies developed in this work for Peano-HASEL actuators can be applied to other types of soft or compliant actuators to enable more versatile and adaptable robotic systems. By incorporating self-sensing capabilities into soft actuators, robotic systems can achieve proprioceptive feedback, allowing for more precise control of position, force, and compliance. This self-awareness can enhance the safety, accuracy, and efficiency of robotic manipulators in various applications.
One potential application of these self-sensing and control strategies is in soft robotics, where compliant actuators are used to interact safely with humans and delicate objects. By integrating self-sensing capabilities, soft robotic systems can adapt to changing environments, detect obstacles, and adjust their behavior accordingly. This would be particularly beneficial in fields such as healthcare, rehabilitation, and human-robot collaboration.
Furthermore, the control strategies developed for the antagonistic robotic shoulder can be extended to multi-actuator systems with complex kinematics, enabling coordinated motion and manipulation tasks. By implementing self-sensing feedback control in these systems, robots can achieve more natural and human-like movements, improving their versatility and adaptability in diverse scenarios.
In conclusion, the self-sensing and control strategies demonstrated in this work have the potential to revolutionize the field of robotics by enabling the development of more intelligent, responsive, and capable robotic systems based on soft and compliant actuators. These advancements could lead to the creation of next-generation robots with enhanced performance and functionality across a wide range of applications.