The musculoskeletal design of animals has inspired a class of robot actuators with a hybrid combination of both rigid and soft components. Such hybrid actuators usually permit the usage of classical theory in rigid-body kinematics for motion analysis. However, the soft components in the design also provide benefits such as inherent safety, light-weight structure, and a high power-to-weight ratio at a cheaper cost. As an integrated design, these hybrid actuators also present varied levels of mechanoreceptive capabilities, making such robots an ideal design for human-centered applications, or unstructured operations for enhanced safety, performance, and robustness, with a significant reduction in cost and weight.
The integrated robot design with rigid and soft components reflects a changing research paradigm towards robotic systems with advanced sensory skills and autonomous feedback in unstructured physical interactions. Such localized interaction holds the potential to generate new representations of the physical interactions for large-scale sensitive data that are difficult to collect using simulation, making it possible to design and train new learning models for the advanced control of hybrid actuators and robot systems.
This Research Topic focuses on reporting recent efforts in the design and mechanoreception of hybrid actuators and the integrated applications of robot systems with both rigid and soft components. Manuscripts can contain results in both theoretical fundamentals and explorative experiments. Contributions should address state-of-the-art design, fabrication, modeling, control, and learning of robots with both rigid and soft components.
We are particularly interested in manuscripts that cover the following subtopics:
• Design: mechanisms and actuation; robots with flexible elements; soft robots; biomimetic and bioinspired robots
• Sensing and Perception: force and tactile sensing; 3-D vision; object recognition; visual servoing; multisensor data fusion
• Control and Manipulation: robot control, motion and force planning, control for manipulation tasks; contact modeling and manipulation; grasping
• Robots at Work: industrial robotics; space robotics; robotics in agriculture and forestry; robotics in construction; robotics in hazardous applications; rehabilitation and healthcare robotics
• Robots and Humans: wearable robots, physical and cognitive human-robot interaction; learning from humans; AI reasoning methods for robotics; neurorobotics
The musculoskeletal design of animals has inspired a class of robot actuators with a hybrid combination of both rigid and soft components. Such hybrid actuators usually permit the usage of classical theory in rigid-body kinematics for motion analysis. However, the soft components in the design also provide benefits such as inherent safety, light-weight structure, and a high power-to-weight ratio at a cheaper cost. As an integrated design, these hybrid actuators also present varied levels of mechanoreceptive capabilities, making such robots an ideal design for human-centered applications, or unstructured operations for enhanced safety, performance, and robustness, with a significant reduction in cost and weight.
The integrated robot design with rigid and soft components reflects a changing research paradigm towards robotic systems with advanced sensory skills and autonomous feedback in unstructured physical interactions. Such localized interaction holds the potential to generate new representations of the physical interactions for large-scale sensitive data that are difficult to collect using simulation, making it possible to design and train new learning models for the advanced control of hybrid actuators and robot systems.
This Research Topic focuses on reporting recent efforts in the design and mechanoreception of hybrid actuators and the integrated applications of robot systems with both rigid and soft components. Manuscripts can contain results in both theoretical fundamentals and explorative experiments. Contributions should address state-of-the-art design, fabrication, modeling, control, and learning of robots with both rigid and soft components.
We are particularly interested in manuscripts that cover the following subtopics:
• Design: mechanisms and actuation; robots with flexible elements; soft robots; biomimetic and bioinspired robots
• Sensing and Perception: force and tactile sensing; 3-D vision; object recognition; visual servoing; multisensor data fusion
• Control and Manipulation: robot control, motion and force planning, control for manipulation tasks; contact modeling and manipulation; grasping
• Robots at Work: industrial robotics; space robotics; robotics in agriculture and forestry; robotics in construction; robotics in hazardous applications; rehabilitation and healthcare robotics
• Robots and Humans: wearable robots, physical and cognitive human-robot interaction; learning from humans; AI reasoning methods for robotics; neurorobotics
