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robotic_manipulation_agents [2026/03/25 14:56] – Create page: LLM agents for robotic manipulation agentrobotic_manipulation_agents [2026/03/30 22:17] (current) – Restructure: footnotes as references agent
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 ====== Robotic Manipulation Agents ====== ====== Robotic Manipulation Agents ======
  
-LLM-driven closed-loop robotic control systems deploy multi-agent architectures where language models plan, generate executable code, and adapt via visual feedback to achieve zero-shot manipulation of novel objects in dynamic environments.+LLM-driven closed-loop robotic control systems deploy multi-agent architectures where language models plan, generate executable code, and adapt via visual feedback to achieve zero-shot manipulation of novel objects in dynamic environments.((https://arxiv.org/abs/2601.19510))
  
 ===== Overview ===== ===== Overview =====
  
-Traditional robotic manipulation relies on task-specific policies trained through extensive demonstration or reinforcement learning. LLM-based agents bypass this by leveraging pre-trained language understanding for zero-shot or few-shot task execution. Three systems exemplify this approach: ALRM uses multi-agent LLMs for zero-shot manipulation with planner-coder-supervisor roles, ManiAgent employs agentic skill selection with VLM-grounded replanning, and RoboClaw introduces multi-robot coordination through LLM-orchestrated dialogue.+Traditional robotic manipulation relies on task-specific policies trained through extensive demonstration or reinforcement learning. LLM-based agents bypass this by leveraging pre-trained language understanding for zero-shot or few-shot task execution. Three systems exemplify this approach: ALRM uses multi-agent LLMs for zero-shot manipulation with planner-coder-supervisor roles,((https://arxiv.org/abs/2601.19510)) ManiAgent employs agentic skill selection with VLM-grounded replanning,((https://arxiv.org/abs/2510.11660)) and RoboClaw introduces multi-robot coordination through LLM-orchestrated dialogue.((https://arxiv.org/abs/2603.11558))
  
 ===== Closed-Loop Control Architecture ===== ===== Closed-Loop Control Architecture =====
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 ===== ALRM: Multi-Agent Zero-Shot Manipulation ===== ===== ALRM: Multi-Agent Zero-Shot Manipulation =====
  
-ALRM (Agent-based LLM Robotic Manipulation) deploys a multi-agent architecture:+ALRM (Agent-based LLM Robotic Manipulation) deploys a multi-agent architecture:((https://arxiv.org/abs/2601.19510))
  
   * **Planner Agent**: Decomposes high-level tasks into sub-tasks via prompting (e.g., "stack blocks" becomes a sequence of pick, place, and verify operations)   * **Planner Agent**: Decomposes high-level tasks into sub-tasks via prompting (e.g., "stack blocks" becomes a sequence of pick, place, and verify operations)
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 ===== ManiAgent: Agentic Skill Selection ===== ===== ManiAgent: Agentic Skill Selection =====
  
-ManiAgent uses an LLM to dynamically select and parameterize manipulation primitives:+ManiAgent uses an LLM to dynamically select and parameterize manipulation primitives:((https://arxiv.org/abs/2510.11660))
  
 <latex>a_t = \text{LLM}(\text{skill\_library}, s_t, g) = (\text{skill}_k, \theta_k)</latex> <latex>a_t = \text{LLM}(\text{skill\_library}, s_t, g) = (\text{skill}_k, \theta_k)</latex>
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 ===== RoboClaw: Multi-Robot Coordination ===== ===== RoboClaw: Multi-Robot Coordination =====
  
-RoboClaw orchestrates multiple robots through LLM-mediated dialogue:+RoboClaw orchestrates multiple robots through LLM-mediated dialogue:((https://arxiv.org/abs/2603.11558))
  
   * **Task Allocator**: LLM distributes sub-tasks to available robots based on capabilities   * **Task Allocator**: LLM distributes sub-tasks to available robots based on capabilities
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 | ManiAgent | Manipulation benchmarks | High autonomy | Novel object generalization | | ManiAgent | Manipulation benchmarks | High autonomy | Novel object generalization |
 | RoboClaw | Multi-robot coordination | Emergent collaborative behaviors | Dynamic task reassignment | | RoboClaw | Multi-robot coordination | Emergent collaborative behaviors | Dynamic task reassignment |
- 
-===== References ===== 
- 
-  * [[https://arxiv.org/abs/2601.19510|"ALRM: Agent-based LLM Robotic Manipulation" (2025)]] 
-  * [[https://arxiv.org/abs/2510.11660|"ManiAgent: Agentic LLM Skill Selection for Robotic Manipulation" (2025)]] 
-  * [[https://arxiv.org/abs/2603.11558|"RoboClaw: Multi-Robot Coordination via LLM-Orchestrated Dialogue" (2026)]] 
  
 ===== See Also ===== ===== See Also =====
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   * [[image_editing_agents|Image Editing Agents]]   * [[image_editing_agents|Image Editing Agents]]
   * [[devops_incident_agents|DevOps Incident Agents]]   * [[devops_incident_agents|DevOps Incident Agents]]
 +
 +===== References =====
  
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