This review summarizes recent advancements in developing actuators and robots with physical intelligence using liquid crystalline polymers (LCPs). LCPs, known for their reversible shape-morphing properties, are promising materials for creating soft robots. The review categorizes studies based on stimulus conditions and explores three main categories: systems responding to changing stimuli, those operating under constant stimuli, and those with learning and logic control capabilities. It highlights the challenges and future directions in this field. LCPs, including liquid crystal networks (LCNs) and liquid crystal elastomers (LCEs), exhibit stimuli-responsive behaviors, such as thermal, optical, and electric actuation. These materials can be actuated by various stimuli, including heat, light, and electric fields, enabling reversible shape changes. The deformation behavior is encoded through spatial alignment, allowing for controlled actuation without digital algorithms, a key feature of physical intelligence. The review discusses applications of LCPs in microfluidics, self-cleaning, smart wearables, and smart windows. It also explores the development of autonomous robots capable of continuous motion and self-sensing. For instance, LCEs can roll, twist, and bend in response to environmental stimuli, demonstrating self-sustained locomotion. Additionally, LCPs have been used to create collective robotic systems, such as swarms, which exhibit coordinated behaviors through interactions. The review also addresses the integration of LCPs as sensors within robotic systems, enabling autonomous path planning and adaptive locomotion. Furthermore, it highlights the potential of LCPs in developing robots with learning and logic control capabilities, such as those that can perform sequential logic control and associative learning through material diffusion and topology changes. Despite significant progress, challenges remain, including improving power density, enhancing energy efficiency, and developing more complex and functional LCP-based systems. Future research aims to overcome these challenges and expand the applications of LCPs in autonomous robotics and smart devices.This review summarizes recent advancements in developing actuators and robots with physical intelligence using liquid crystalline polymers (LCPs). LCPs, known for their reversible shape-morphing properties, are promising materials for creating soft robots. The review categorizes studies based on stimulus conditions and explores three main categories: systems responding to changing stimuli, those operating under constant stimuli, and those with learning and logic control capabilities. It highlights the challenges and future directions in this field. LCPs, including liquid crystal networks (LCNs) and liquid crystal elastomers (LCEs), exhibit stimuli-responsive behaviors, such as thermal, optical, and electric actuation. These materials can be actuated by various stimuli, including heat, light, and electric fields, enabling reversible shape changes. The deformation behavior is encoded through spatial alignment, allowing for controlled actuation without digital algorithms, a key feature of physical intelligence. The review discusses applications of LCPs in microfluidics, self-cleaning, smart wearables, and smart windows. It also explores the development of autonomous robots capable of continuous motion and self-sensing. For instance, LCEs can roll, twist, and bend in response to environmental stimuli, demonstrating self-sustained locomotion. Additionally, LCPs have been used to create collective robotic systems, such as swarms, which exhibit coordinated behaviors through interactions. The review also addresses the integration of LCPs as sensors within robotic systems, enabling autonomous path planning and adaptive locomotion. Furthermore, it highlights the potential of LCPs in developing robots with learning and logic control capabilities, such as those that can perform sequential logic control and associative learning through material diffusion and topology changes. Despite significant progress, challenges remain, including improving power density, enhancing energy efficiency, and developing more complex and functional LCP-based systems. Future research aims to overcome these challenges and expand the applications of LCPs in autonomous robotics and smart devices.