Other · AI and Machine Learning
Debiut publiczny (z robotem Mobo)·
MoAgent is a proprietary, agentic artificial-intelligence system developed by AiMOGA Robotics — the embodied-AI robotics brand of China's Chery Group. It acts as the robot's decision layer (its "brain"): it interprets complex, high-level instructions, breaks them into concrete steps and plans multi-step tasks, rather than merely reacting to isolated commands.
The system combines spatial perception with multimodal interaction (voice, vision, conversational context), object recognition, dynamic obstacle avoidance and memory of individual users’ habits and preferences (with privacy protection). MoAgent is neither a foundation model nor low-level firmware — it is a task-orchestration layer.
MoAgent powers the Mobo home-companion humanoid, which was unveiled and opened for global pre-orders at the Chery International User Summit in October 2026. In parallel, AiMOGA develops the MoNet vision-language model (6B, Mixture of Experts, deployed on-device) and draws on Chery Group’s CheryMind model; the exact architectural relationships between MoAgent, MoNet and CheryMind have not been publicly documented.
A category of robotics software known as agentic OS — the top-most layer of a humanoid's software stack that manages the agent's lifecycle: multi-modal perception, task reasoning, skill selection, motion planning, end-effector coordination, VLA model invocation, and execution supervision. It replaces a scattered set of scripts with an application layer that makes decisions itself.
Physical AI platforms are software products that connect physical robots and industrial production processes with artificial intelligence models. Unlike a pure SDK or middleware, a Physical AI Platform ships as an end-to-end stack: perception, task planning, process parameter optimization, multi-robot coordination and operator UI. They target use cases such as surface treatment (grinding, painting, polishing), inspection, assembly and packing — where business value comes from combining hardware, AI and domain knowledge.
A robotics software type dedicated to shaping a robot's social-linguistic layer. It covers personality engines (persona engines), voice and style-of-speech management systems, dedicated knowledge-base authoring tools, and dialogue frameworks. Unlike general-purpose LLMs or chat assistants, a robot persona engine is tied to a specific embodiment (humanoid, quadruped, social robot) and its use cases (e.g. reception, retail sales, financial advisory, patient care). It typically sits on top of a foundation model or VLA layer, adding personality profile, safety constraints, branding, and deployment-specific knowledge.
The Physical AI orchestration role describes software that ties perception, AI decisions and multi-robot control into a single production workflow. The orchestration layer assigns specific tasks to specific machines, monitors the real-time state of the process, tunes execution parameters (e.g. contact force, feed rate, motion trajectory) and reports production KPIs. It typically sits above the robot control layer and below ERP/MES.
Functional role for robotics software focused on the human-robot interaction (HRI) layer. It includes building the robot's persona (personality), a consistent style of speech, voice selection, social and emotional behaviour, dedicated knowledge bases for specific industries (e.g. reception, sales, advisory, care), and interaction-scenario management. Complementary to the roles of high-level compute (task planning) and robot learning (policy training).
AiMOGA's (Chery Group) embodied-AI software ecosystem: the MoAgent agentic system and the MoNet vision-language model, powering the Mornine and Mobo humanoids.
Mobo — AiMOGA's first consumer home-companion humanoid (global pre-orders from October 2026).
No public community — a closed, proprietary AiMOGA system.
License family: Proprietary – Commercial
First public presentation of MoAgent as the AI system powering the Mobo humanoid; global pre-orders opened at the Chery International User Summit.
