Alternatives to Physical Intelligence

Omni-bodied robotic intelligence: one AI brain to control any robot for any physical task

Rhoda AI builds general-purpose robot foundation models with FutureVision video-predictive control for factory and warehouse work.

A foundation model for physical intelligence, controlling robots and industrial machinery.

Open-source simulated benchmark for language-conditioned, long-horizon robot manipulation research.

Open-source Python SDK and managed cloud platform to train and deploy physical AI on robots.

Open-source C++ toolkit with SLAM, perception, and 3D vision algorithms for robotics research.

Autonomous manipulation skills for industrial robots, verified on your cell.

Zeon Systems turns natural language experiment prompts into simulated, robot-executed wet lab protocols on your existing instruments.

License proven L4 autonomous driving technology for robotaxis, fleets, and personal vehicles.

Open-source robot dog and cat kits you assemble, code, and program in Python, C++, or block-based tools.

Tactile capture hardware that records touch-aware demonstrations for dexterous robot training.

Real-world egocentric video and robot data for embodied AI training.

Open-source Unreal Engine plugin for synthetic data generation and computer vision research.

AI observability for cyber-physical systems, tracing agent decisions in the real world

AI foundation model for real-time physics simulation

Open source dev kit for AI-native robotics with leader-follower teleoperation.

Modular humanoid robot platform for builders

Mapless embodied AI driving software that brings L2-to-L4 autonomy to any vehicle, anywhere.

Open-source simulator for developing, training, and validating autonomous driving systems.

Modular LiDAR SLAM framework for ROS 2 — free for research, Pro for products

Open benchmarks and fusion pipeline for V2V cooperative perception in autonomous driving research.

Causal world model for real-time, interactive simulation with state-of-the-art physics accuracy.

Raw radar data, real or synthetic, for end-to-end autonomous driving.

Multimodal real-world human data for training embodied AI