Robotic hand delicately holding a flower

Robotic Hands: The Future of Remote Interaction

Lena Kashyap in Tech & Innovation September 2025 • 3 min read.

"Explore how advanced teleoperation systems are revolutionizing industries, offering precision and safety in handling tasks from a distance."

In recent years, the world of robotics has witnessed an extraordinary surge in the use of robot manipulators, designed to act as human hand substitutes in a multitude of tasks across diverse fields. From manufacturing to surgery, these mechanical marvels are increasingly capable, precise, and adaptable.

Robot manipulators are generally divided based on stiffness and actuation methods. Rigid robots are known for their precision but lack compliance. Soft robots are safer for human interaction but have limited strength. Combining the best of both worlds, underactuated manipulators offer a balance of compliance, robustness, and controllability.

Teleoperation systems have emerged as the next frontier in robotics. These systems enable humans to control robots from a distance, enhancing performance through real-time feedback. As the technology improves, so does the potential for robot-assisted tasks to become more intricate and efficient.

What Makes a Good Teleoperation System?

Robotic hand delicately holding a flower

A well-designed teleoperation system hinges on accurate synchronization, reasonable force feedback, and precise dynamic models. Synchronization ensures that multiple robots move in unison, while force feedback allows the operator to perceive the remote environment. Accurate dynamic models enable the system to anticipate and respond to different conditions effectively.

Sliding mode control (SMC) algorithms have greatly improved transient-state control performance, enhancing the system's ability to handle disturbances and uncertainties. Fuzzy logic models can be used when accurate mathematical functions are difficult to achieve, providing robustness and adaptability.

Accurate Position Synchronization: Ensuring multiple robots move in perfect harmony.
Reasonable Force Feedback: Allowing operators to feel and react to the remote environment.
Accurate Dynamic Models: Enhancing robot responsiveness and adaptability.

Interval Type-2 Takagi-Sugeno (T-S) fuzzy models offer advanced control. They use intervals instead of crisp numbers for fuzzy memberships, providing additional design degrees to describe inexactness and increase robustness. This model is effective in managing noises and disturbances within the system.

Looking Ahead: The Future of Multilateral Teleoperation

The advancements in multilateral teleoperation systems promise a future where robots can perform increasingly complex tasks with greater precision and safety. As technology evolves, these systems will become more flexible, reliable, and integrated into various aspects of industry and daily life. Continued research and development will undoubtedly unlock even greater potential, making robots indispensable partners in navigating the challenges of tomorrow.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1109/tcyb.2018.2828503, Alternate LINK

Title: Multilateral Teleoperation With New Cooperative Structure Based On Reconfigurable Robots And Type-2 Fuzzy Logic

Subject: Electrical and Electronic Engineering

Journal: IEEE Transactions on Cybernetics

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Authors: Da Sun, Qianfang Liao, Xiaoyi Gu, Changsheng Li, Hongliang Ren

Published: 2019-08-01

Everything You Need To Know

What are robot manipulators and in what areas are they used?

Robot manipulators are mechanical devices designed to act as human hand substitutes across various fields. They're utilized in manufacturing, surgery, and other areas where precise, adaptable, and sometimes remote handling is required. The design and control of these manipulators vary based on the tasks, from rigid robots prioritizing precision to soft robots prioritizing safety.

What are the key differences between rigid, soft, and underactuated robot manipulators?

Rigid robots are known for their precision but lack compliance. Soft robots are safer for human interaction but have limited strength. Underactuated manipulators combine the best of both worlds, offering a balance of compliance, robustness, and controllability. This balance is crucial for applications needing both precision and safety, especially in dynamic environments.

What are teleoperation systems and how do they improve robotic capabilities?

Teleoperation systems enable humans to control robots from a distance. They improve robotic capabilities by allowing for real-time control and feedback, which enhances the precision, efficiency, and adaptability of robot-assisted tasks. Accurate synchronization, reasonable force feedback, and precise dynamic models are crucial components for effective teleoperation.

What factors make a good teleoperation system, and how do specific models, like Interval Type-2 Takagi-Sugeno fuzzy models, improve control?

A well-designed teleoperation system relies on accurate synchronization, reasonable force feedback, and precise dynamic models. Interval Type-2 Takagi-Sugeno (T-S) fuzzy models enhance control by using intervals instead of crisp numbers for fuzzy memberships, providing additional design degrees to describe inexactness and increase robustness. This model effectively manages noises and disturbances within the system, improving overall performance and stability.

How do sliding mode control (SMC) algorithms and fuzzy logic models enhance teleoperation systems, and what are the implications for handling uncertainties and disturbances?

Sliding mode control (SMC) algorithms improve transient-state control performance, allowing the system to handle disturbances and uncertainties more effectively. Fuzzy logic models are used when accurate mathematical functions are difficult to achieve, providing robustness and adaptability. Together, these methods allow teleoperation systems to operate reliably in uncertain and dynamic environments, improving their versatility and practical application.