Papers Task and Motion Planning
“Task and Motion Planning” 태그가 달린 논문 86편 · 필터 해제
Language-Grounded Hierarchical Planning and Execution with Multi-Robot 3D Scene Graphs
In this paper, we introduce a multi-robot system that integrates mapping, localization, and task and motion planning (TAMP) enabled by 3D scene graphs to execute complex instructions expressed in natural language. Our sy…
Language ModelingLanguage ModellingLarge Language ModelMotion Planning+1Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search
The problem of relocating a set of objects to designated areas amidst movable obstacles can be framed as a Geometric Task and Motion Planning (G-TAMP) problem, a subclass of task and motion planning (TAMP). Traditional a…
Common Sense ReasoningMotion PlanningTask and Motion PlanningTask PlanningUnderstanding Physical Properties of Unseen Deformable Objects by Leveraging Large Language Models and Robot Actions
In this paper, we consider the problem of understanding the physical properties of unseen objects through interactions between the objects and a robot. Handling unseen objects with special properties such as deformabilit…
Motion PlanningTask and Motion PlanningTask PlanningGrounded Vision-Language Interpreter for Integrated Task and Motion Planning
While recent advances in vision-language models (VLMs) have accelerated the development of language-guided robot planners, their black-box nature often lacks safety guarantees and interpretability crucial for real-world …
Motion PlanningTask and Motion PlanningTask PlanningFrom Motion to Behavior: Hierarchical Modeling of Humanoid Generative Behavior Control
Human motion generative modeling or synthesis aims to characterize complicated human motions of daily activities in diverse real-world environments. However, current research predominantly focuses on either low-level, sh…
Motion GenerationMotion PlanningTask and Motion PlanningOptimal Task and Motion Planning for Autonomous Systems Using Petri Nets
This study deals with the problem of task and motion planning of autonomous systems within the context of high-level tasks. Specifically, a task comprises logical requirements (conjunctions, disjunctions, and negations) …
Computational EfficiencyMotion PlanningTask and Motion PlanningMulti-step manipulation task and motion planning guided by video demonstration
This work aims to leverage instructional video to solve complex multi-step task-and-motion planning tasks in robotics. Towards this goal, we propose an extension of the well-established Rapidly-Exploring Random Tree (RRT…
Motion PlanningTask and Motion PlanningLeveraging Pre-trained Large Language Models with Refined Prompting for Online Task and Motion Planning
With the rapid advancement of artificial intelligence, there is an increasing demand for intelligent robots capable of assisting humans in daily tasks and performing complex operations. Such robots not only require task …
Large Language ModelMotion PlanningTask and Motion PlanningTask PlanningA Task and Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networks
In this paper, we present an approach for integrated task and motion planning based on an AND/OR graph network, which is used to represent task-level states and actions, and we leverage it to implement different classes …
Motion PlanningTask and Motion PlanningCuriosity-Driven Imagination: Discovering Plan Operators and Learning Associated Policies for Open-World Adaptation
Adapting quickly to dynamic, uncertain environments-often called "open worlds"-remains a major challenge in robotics. Traditional Task and Motion Planning (TAMP) approaches struggle to cope with unforeseen changes, are d…
Motion PlanningTask and Motion PlanningCode-as-Symbolic-Planner: Foundation Model-Based Robot Planning via Symbolic Code Generation
Recent works have shown great potentials of Large Language Models (LLMs) in robot task and motion planning (TAMP). Current LLM approaches generate text- or code-based reasoning chains with sub-goals and action plans. How…
Code GenerationCommon Sense ReasoningMotion PlanningTask and Motion PlanningRisk-aware Integrated Task and Motion Planning for Versatile Snake Robots under Localization Failures
Snake robots enable mobility through extreme terrains and confined environments in terrestrial and space applications. However, robust perception and localization for snake robots remain an open challenge due to the prox…
Motion PlanningTask and Motion PlanningTowards Robust and Secure Embodied AI: A Survey on Vulnerabilities and Attacks
Embodied AI systems, including robots and autonomous vehicles, are increasingly integrated into real-world applications, where they encounter a range of vulnerabilities stemming from both environmental and system-level f…
Adversarial AttackAutonomous VehiclesDecision MakingMotion Planning+2Planning with affordances: Integrating learned affordance models and symbolic planning
Intelligent agents working in real-world environments must be able to learn about the environment and its capabilities which enable them to take actions to change to the state of the world to complete a complex multi-ste…
Motion PlanningTask and Motion PlanningZero-shot Robotic Manipulation with Language-guided Instruction and Formal Task Planning
Robotic manipulation is often challenging due to the long-horizon tasks and the complex object relationships. A common solution is to develop a task and motion planning framework that integrates planning for high-level t…
Motion PlanningTask and Motion PlanningTask PlanningWorld KnowledgeOntology-driven Prompt Tuning for LLM-based Task and Motion Planning
Performing complex manipulation tasks in dynamic environments requires efficient Task and Motion Planning (TAMP) approaches, which combine high-level symbolic plan with low-level motion planning. Advances in Large Langua…
Motion PlanningTask and Motion PlanningTask Planningλ: A Benchmark for Data-Efficiency in Long-Horizon Indoor Mobile Manipulation Robotics
Learning to execute long-horizon mobile manipulation tasks is crucial for advancing robotics in household and workplace settings. However, current approaches are typically data-inefficient, underscoring the need for impr…
BenchmarkingDiversityLearning to ExecuteMotion Planning+1SPIRE: Synergistic Planning, Imitation, and Reinforcement Learning for Long-Horizon Manipulation
Robot learning has proven to be a general and effective technique for programming manipulators. Imitation learning is able to teach robots solely from human demonstrations but is bottlenecked by the capabilities of the d…
Imitation LearningMotion Planningreinforcement-learningReinforcement Learning+2VLM See, Robot Do: Human Demo Video to Robot Action Plan via Vision Language Model
Vision Language Models (VLMs) have recently been adopted in robotics for their capability in common sense reasoning and generalizability. Existing work has applied VLMs to generate task and motion planning from natural l…
Common Sense ReasoningLanguage ModelingLanguage ModellingMotion Planning+3Interpretable Responsibility Sharing as a Heuristic for Task and Motion Planning
This article introduces a novel heuristic for Task and Motion Planning (TAMP) named Interpretable Responsibility Sharing (IRS), which enhances planning efficiency in domestic robots by leveraging human-constructed enviro…
Decision MakingMotion PlanningTask and Motion Planning