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A Review of Multi-Robot Systems and Soft Robotics: Challenges and Opportunities
Juan C Tejada1,2, Alejandro Toro-Ossaba2, Alexandro López-Gonzalez1
1Departament of Engineering Studies for Innovation, Universidad Iberoamericana Ciudad de México, Prolongación Paseo de la Reforma 880, Colonia Lomas de Santa Fé, Ciudad de México 01219, Mexico.
This review explores the integration of Multi-Robot Systems (MRSs) and soft robotics, highlighting advancements in adaptive control and coordination for complex tasks. It addresses challenges and opportunities in developing collaborative robotic systems.
Area of Science:
- Robotics
- Artificial Intelligence
- Materials Science
Background:
- Multi-Robot Systems (MRS) leverage distributed AI for coordinated tasks like navigation and transportation.
- Soft robotics utilizes flexible materials for enhanced adaptability in unstructured environments.
- Existing reviews often treat these fields separately, overlooking synergistic potential.
Purpose of the Study:
- To investigate the integration of Multi-Robot Systems and soft robotics.
- To identify key challenges and emerging opportunities at the intersection of these fields.
- To provide insights into recent advancements in locomotion, coordination, and simulation.
Main Methods:
- Comprehensive literature review of recent advancements in MRS and soft robotics.
- Analysis of integration challenges, including nonlinear dynamics and adaptive control.
- Synthesis of findings on locomotion, coordination, and simulation techniques.
Main Results:
- Identified key challenges in integrating MRS and soft robotics, such as nonlinear dynamics and hyper-redundant configurations.
- Highlighted recent advancements in locomotion, coordination, and simulation for adaptive robotic systems.
- Showcased emerging opportunities for collaborative and adaptable robotic applications.
Conclusions:
- The integration of Multi-Robot Systems and soft robotics presents significant opportunities for developing advanced adaptive and collaborative systems.
- Addressing challenges in nonlinear dynamics and adaptive control is crucial for realizing the full potential of integrated systems.
- Further research in locomotion, coordination, and simulation will drive innovation in diverse robotic applications.
