Autonomous robots are becoming a promising solution to perform tasks without supervision in complex environments. In recent years, remarkable advancements have been achieved in the independent operation of autonomous robots without human control or intervention. However, the challenge of achieving robust locomotion, sensing, and manipulation in humanoid robots persists. Overcoming this challenge requires three essential components: the integration of smart materials-based actuators and sensors to enhance the level of autonomy and operational efficiency, robust locomotion combined with spatial reasoning to navigate through constrained spaces, and sensor fusion to perceive and respond to moving obstacles and engage in human interaction. By integrating novel findings from these key aspects, the full potential of autonomous robots can be unlocked, enabling them to transition from laboratory experiments to practical contributors in human society. To become a general-purpose platform to provide services in actual applications, autonomous robots must possess both physical/computational intelligence and advanced control autonomy to interact independently with complex, often unstructured environments.

This Research Topic aims to explore the development of advanced intelligent autonomous robots. Specifically, it seeks to address the integration of smart materials and mechanisms for actuation and sensing, the utilization of direct drive motors with high torque density and energy recovery capabilities, and the implementation of model-based numerical optimization for real-time control. The goal is to enhance the multifunctionalities, payload capacity, and battery life of autonomous robots, while also improving their adaptability and resilience in performing locomotion and manipulation tasks. By focusing on these objectives, the research aims to facilitate the successful deployment of autonomous robots in real-world scenarios.

To gather further insights into the development of intelligent autonomous robots, we welcome articles addressing, but not limited to, the following themes:
- Design and Instrumentation
- Integrated actuation and sensing
- Smart materials and mechanisms
- Power-efficient actuators
- Tactile/visual/motion sensors
- Advanced Motion Control
- Model predictive control (MPC) of legged robots
- Humanoid/Quadrupedal whole-body control
- Trajectory optimization
- Reinforcement learning
- Intelligent Perception and Planning
- Multi-sensor fusion and state estimation
- Dynamic motion planning with moving obstacles
- Visual servoing
- Terrain-aware locomotion

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Frontiers in Robotics and AI

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