We invite researchers to submit proposals for cutting-edge research in Embodied Artificial Intelligence (AI).

Embodied agents such as mobile robots, manipulators, and multi-modal perception systems are redefining the boundaries of autonomy. This RFP aims to accelerate breakthroughs across foundational algorithms, robust real-world transfer, and scalable deployment for embodied AI.

Research Focus Areas

We welcome proposals addressing — but not limited to — the following topics:

Manipulation

• Dexterous object manipulation

• Single-arm or Bimanual manipulation and coordinated control for robotic arms

• Multi-Agent Task Planning in Robotic Systems

Navigation

• Autonomous navigation for mobile robots in complex environments

• Learning-based planning under uncertainty

• Cross-domain adaptation for visual and sensor-based navigation

• Large Language Model (LLM)-driven planning and reasoning for navigation tasks

Sim2Real & Domain Adaptation

• Transferring policies from simulation to real-world

• Data-efficient adaptation methods

• Robustness against real-world distribution shifts

Key Learning Algorithms

• Imitation Learning and Behavior Cloning for embodied agents

• Deep Reinforcement Learning for long-horizon tasks

• Self-supervised and unsupervised representation learning for control

Efficiency & Deployment

• Resource-efficient inference for real-time robotic control

• Deployment strategies for Edge AI and onboard computation

• Model compression and latency-aware optimization

Vision-Language-Action Models & Fine-Tuning

• Integrating Vision-Language-Action Models (VLAs) for embodied reasoning

• Fine-tuning VLA models for perception-action loops

• Instruction following, semantic grounding, and multi-modal learning in robotics