Papers Robot Task Planning
“Robot Task Planning” 태그가 달린 논문 67편 · 필터 해제
PO-PDDL: Learning Symbolic POMDPs from Visual Demonstrations for Robot Planning Under Uncertainty
Real-world robot task planning must operate under both stochastic action execution and partial observability, yet constructing Partially Observable Markov Decision Process (POMDP) models for real robotics domains remains…
Robot Task PlanningSafe reinforcement learning with online filtering for fatigue-predictive human-robot task planning and allocation in production
Human-robot collaborative manufacturing, a core aspect of Industry 5.0, emphasizes ergonomics to enhance worker well-being. This paper addresses the dynamic human-robot task planning and allocation (HRTPA) problem, which…
Reinforcement LearningRobot Task PlanningA hierarchical spatial-aware algorithm with efficient reinforcement learning for human-robot task planning and allocation in production
In advanced manufacturing systems, humans and robots collaborate to conduct the production process. Effective task planning and allocation (TPA) is crucial for achieving high production efficiency, yet it remains challen…
Reinforcement LearningRobot Task PlanningRo-SLM: Onboard Small Language Models for Robot Task Planning and Operation Code Generation
Recent advances in large language models (LLMs) provide robots with contextual reasoning abilities to comprehend human instructions. Yet, current LLM-enabled robots typically depend on cloud-based models or high-performa…
Robot Task PlanningCode GenerationIndoorR2X: Indoor Robot-to-Everything Coordination with LLM-Driven Planning
Although robot-to-robot (R2R) communication improves indoor scene understanding beyond what a single robot can achieve, R2R alone cannot overcome partial observability without substantial exploration overhead or scaling …
Robot Task PlanningScene UnderstandingContextual Graph Representations for Task-Driven 3D Perception and Planning
Recent advances in computer vision facilitate fully automatic extraction of object-centric relational representations from visual-inertial data. These state representations, dubbed 3D scene graphs, are a hierarchical dec…
Robot Task PlanningMultimodal Behavior Tree Generation: A Small Vision-Language Model for Robot Task Planning
Large and small language models have been widely used for robotic task planning. At the same time, vision-language models (VLMs) have successfully tackled problems such as image captioning, scene understanding, and visua…
parameter-efficient fine-tuningVisual Question AnsweringRobot Task PlanningScene UnderstandingIMR-LLM: Industrial Multi-Robot Task Planning and Program Generation using Large Language Models
In modern industrial production, multiple robots often collaborate to complete complex manufacturing tasks. Large language models (LLMs), with their strong reasoning capabilities, have shown potential in coordinating rob…
Robot Task PlanningHierarchical LLM-Based Multi-Agent Framework with Prompt Optimization for Multi-Robot Task Planning
Multi-robot task planning requires decomposing natural-language instructions into executable actions for heterogeneous robot teams. Conventional Planning Domain Definition Language (PDDL) planners provide rigorous guaran…
Robot Task PlanningUniPlan: Vision-Language Task Planning for Mobile Manipulation with Unified PDDL Formulation
Integration of VLM reasoning with symbolic planning has proven to be a promising approach to real-world robot task planning. Existing work like UniDomain effectively learns symbolic manipulation domains from real-world d…
Computational EfficiencyRobot Task PlanningEmboTeam: Grounding LLM Reasoning into Reactive Behavior Trees via PDDL for Embodied Multi-Robot Collaboration
In embodied artificial intelligence, enabling heterogeneous robot teams to execute long-horizon tasks from high-level instructions remains a critical challenge. While large language models (LLMs) show promise in instruct…
Robot Task PlanningPROTEA: Securing Robot Task Planning and Execution
Robots need task planning methods to generate action sequences for complex tasks. Recent work on adversarial attacks has revealed significant vulnerabilities in existing robot task planners, especially those built on fou…
Robot Task PlanningVision-Language-Policy Model for Dynamic Robot Task Planning
Bridging the gap between natural language commands and autonomous execution in unstructured environments remains an open challenge for robotics. This requires robots to perceive and reason over the current task scene thr…
Robot Task PlanningLEO-RobotAgent: A General-purpose Robotic Agent for Language-driven Embodied Operator
We propose LEO-RobotAgent, a general-purpose language-driven intelligent agent framework for robots. Under this framework, LLMs can operate different types of robots to complete unpredictable complex tasks across various…
Robot Task PlanningRoboGPT-R1: Enhancing Robot Task Planning with Reinforcement Learning
Improving the reasoning capabilities of embodied agents is crucial for robots to complete complex human instructions in long-view manipulation tasks successfully. Despite the success of large language models and vision l…
Reinforcement LearningRobot Task PlanningMaximal Adaptation, Minimal Guidance: Permissive Reactive Robot Task Planning with Humans in the Loop
We present a novel framework for human-robot \emph{logical} interaction that enables robots to reliably satisfy (infinite horizon) temporal logic tasks while effectively collaborating with humans who pursue independent a…
Robot Task PlanningRobotFleet: An Open-Source Framework for Centralized Multi-Robot Task Planning
Coordinating heterogeneous robot fleets to achieve multiple goals is challenging in multi-robot systems. We introduce an open-source and extensible framework for centralized multi-robot task planning and scheduling that …
Robot Task PlanningMulti-Robot Task Planning for Multi-Object Retrieval Tasks with Distributed On-Site Knowledge via Large Language Models
It is crucial to efficiently execute instructions such as "Find an apple and a banana" or "Get ready for a field trip," which require searching for multiple objects or understanding context-dependent commands. This study…
Robot Task PlanningUniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning
Robotic task planning in real-world environments requires reasoning over implicit constraints from language and vision. While LLMs and VLMs offer strong priors, they struggle with long-horizon structure and symbolic grou…
Robot Task PlanningRobot ManipulationREI-Bench: Can Embodied Agents Understand Vague Human Instructions in Task Planning?
Robot task planning decomposes human instructions into executable action sequences that enable robots to complete a series of complex tasks. Although recent large language model (LLM)-based task planners achieve amazing …
Large Language ModelRobot Task PlanningTask Planning