Papers Task Planning
“Task Planning” 태그가 달린 논문 344편 · 필터 해제
Adaptive Interactive Navigation of Quadruped Robots using Large Language Models
Robotic navigation in complex environments remains a critical research challenge. Traditional navigation methods focus on optimal trajectory generation within free space, struggling in environments lacking viable paths t…
Motion PlanningTask PlanningREMAC: Self-Reflective and Self-Evolving Multi-Agent Collaboration for Long-Horizon Robot Manipulation
Vision-language models (VLMs) have demonstrated remarkable capabilities in robotic planning, particularly for long-horizon tasks that require a holistic understanding of the environment for task decomposition. Existing m…
Robot ManipulationTask PlanningData-Agnostic Robotic Long-Horizon Manipulation with Vision-Language-Guided Closed-Loop Feedback
Recent advances in language-conditioned robotic manipulation have leveraged imitation and reinforcement learning to enable robots to execute tasks from human commands. However, these methods often suffer from limited gen…
Task PlanningMulti-agent Application System in Office Collaboration Scenarios
This paper introduces a multi-agent application system designed to enhance office collaboration efficiency and work quality. The system integrates artificial intelligence, machine learning, and natural language processin…
Decision MakingTask PlanningLLM+MAP: Bimanual Robot Task Planning using Large Language Models and Planning Domain Definition Language
Bimanual robotic manipulation provides significant versatility, but also presents an inherent challenge due to the complexity involved in the spatial and temporal coordination between two hands. Existing works predominan…
In-Context LearningRobot Task PlanningTask PlanningSafety Aware Task Planning via Large Language Models in Robotics
The integration of large language models (LLMs) into robotic task planning has unlocked better reasoning capabilities for complex, long-horizon workflows. However, ensuring safety in LLM-driven plans remains a critical c…
Task PlanningIntelligent Spatial Perception by Building Hierarchical 3D Scene Graphs for Indoor Scenarios with the Help of LLMs
This paper addresses the high demand in advanced intelligent robot navigation for a more holistic understanding of spatial environments, by introducing a novel system that harnesses the capabilities of Large Language Mod…
ObjectRobot NavigationTask PlanningMitigating Cross-Modal Distraction and Ensuring Geometric Feasibility via Affordance-Guided, Self-Consistent MLLMs for Food Preparation Task Planning
We study Multimodal Large Language Models (MLLMs) with in-context learning for food preparation task planning. In this context, we identify two key challenges: cross-modal distraction and geometric feasibility. Cross-mod…
Collision AvoidanceIn-Context LearningTask PlanningExploring 3D Activity Reasoning and Planning: From Implicit Human Intentions to Route-Aware Planning
3D activity reasoning and planning has attracted increasing attention in human-robot interaction and embodied AI thanks to the recent advance in multimodal learning. However, most existing studies are facing two common c…
Scene SegmentationTask PlanningBeing-0: A Humanoid Robotic Agent with Vision-Language Models and Modular Skills
Building autonomous robotic agents capable of achieving human-level performance in real-world embodied tasks is an ultimate goal in humanoid robot research. Recent advances have made significant progress in high-level co…
Task PlanningWorld Modeling Makes a Better Planner: Dual Preference Optimization for Embodied Task Planning
Recent advances in large vision-language models (LVLMs) have shown promise for embodied task planning, yet they struggle with fundamental challenges like dependency constraints and efficiency. Existing approaches either …
Task PlanningSurgicalVLM-Agent: Towards an Interactive AI Co-Pilot for Pituitary Surgery
Image-guided surgery demands adaptive, real-time decision support, yet static AI models struggle with structured task planning and providing interactive guidance. Large vision-language models (VLMs) offer a promising sol…
Activity RecognitionAnatomyQuestion AnsweringSegmentation+4General-Purpose Aerial Intelligent Agents Empowered by Large Language Models
The emergence of large language models (LLMs) opens new frontiers for unmanned aerial vehicle (UAVs), yet existing systems remain confined to predefined tasks due to hardware-software co-design challenges. This paper pre…
Motion PlanningScene UnderstandingState EstimationTask PlanningInvestigating the Effectiveness of a Socratic Chain-of-Thoughts Reasoning Method for Task Planning in Robotics, A Case Study
Large language models (LLMs) have demonstrated unprecedented capability in reasoning with natural language. Coupled with this development is the emergence of embodied AI in robotics. Despite showing promise for verbal an…
Code GenerationTask PlanningZero-Shot LearningSelf-Corrective Task Planning by Inverse Prompting with Large Language Models
In robot task planning, large language models (LLMs) have shown significant promise in generating complex and long-horizon action sequences. However, it is observed that LLMs often produce responses that sound plausible …
Robot Task PlanningTask PlanningGraphormer-Guided Task Planning: Beyond Static Rules with LLM Safety Perception
Recent advancements in large language models (LLMs) have expanded their role in robotic task planning. However, while LLMs have been explored for generating feasible task sequences, their ability to ensure safe task exec…
Task PlanningSTAR: A Foundation Model-driven Framework for Robust Task Planning and Failure Recovery in Robotic Systems
Modern robotic systems, deployed across domains from industrial automation to domestic assistance, face a critical challenge: executing tasks with precision and adaptability in dynamic, unpredictable environments. To add…
Information RetrievalKnowledge GraphsTask PlanningSafe LLM-Controlled Robots with Formal Guarantees via Reachability Analysis
The deployment of Large Language Models (LLMs) in robotic systems presents unique safety challenges, particularly in unpredictable environments. Although LLMs, leveraging zero-shot learning, enhance human-robot interacti…
Autonomous NavigationNavigateTask PlanningZero-Shot LearningImproving Retrospective Language Agents via Joint Policy Gradient Optimization
In recent research advancements within the community, large language models (LLMs) have sparked great interest in creating autonomous agents. However, current prompt-based agents often heavily rely on large-scale LLMs. M…
Decision MakingImitation LearningTask PlanningCLEA: Closed-Loop Embodied Agent for Enhancing Task Execution in Dynamic Environments
Large Language Models (LLMs) exhibit remarkable capabilities in the hierarchical decomposition of complex tasks through semantic reasoning. However, their application in embodied systems faces challenges in ensuring reli…
Task Planning