Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 23 for “"Task and Motion Planning"”.
-
Efficiency and abstraction in task and motion planning
Modern robots are capable of complex and highly dynamic behaviors, yet the decisionmaking algorithms that drive them struggle to solve problems involving complex behaviors like manipulation. The combination of continuous and discrete dynamics induced by contact creates severe computational …
-
A Constraint-Based Approach to Reactive Task and Motion Planning
This thesis presents a novel and scalable approach for Reactive Task and Motion Planning. We consider changing environments with uncontrollable agents, where the robot needs a policy to respond correctly in the infinite interaction with the environment. Our approach operates on task and motion …
-
Multi-robot task and motion planning in hybrid state spaces
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms
-
Generative multi-robot task and motion planning over long horizons
The state of the art practice in robotics planning is to script behaviors manually, where each behavior is typically precomputed in advance. However, in order for robots to be able to act robustly and adapt to novel situations, they need to be able to plan sequences of behaviors and activities …
-
Generalizable Robot Manipulation through Task and Motion Planning and Interactive Perception
… It should be able to generalize to different tasks that involve different objects in varying backgrounds and configurations. In this thesis, we will move towards this goal from two perspectives. We will first present a strategy for designing a robot manipulation system that can generalize to a …
-
Sampling-Based Robot Task and Motion Planning in the Real World
… program a robot to autonomously complete complex tasks in a variety of real-world settings involving different environments, objects, manipulation skills, degrees of observability, initial states, and goal objectives. In order to successfully generalize across these settings, we take a model-based …
-
Learning Compositional Abstract Models Incrementally for Efficient Bilevel Task and Motion Planning
In robotic domains featuring continuous state and action spaces, planning in long-horizon task is fundamentally hard, even when the transition model is deterministic and known. One way to alleviate this challenge is to perform bilevel planning with abstractions, where a high-level search for …
-
Creation of tools for manipulation tasks through Task and motion Planning using differentiable physics
… of dynamic physical manipulations within a Task And Motion Planning (TAMP) framework to achieve a subset of sequential manipulation tasks involving tools. The work, in part, mimics the human ability to plan using an 'intuitive physics engine' [2] by using physics-based primitives in task …
-
Learning Diffusion Models to Enable Efficient Sampling for Task and Motion Planning on a Panda Robot
A search then sample approach to bilevel planning in the context of task and motion planning is one method of effectively solving multi-step robotics problems. In this planning framework, high-level plans of abstract actions are refined into low-level continuous transitions by sampling controller …
-
Heuristic search for manipulation planning
… many objects present substantial challenges for planning algorithms due to the high dimensionality and multi-modality of the search space. Symbolic task planners can efficiently construct plans involving many entities but cannot incorporate the constraints from geometry and kinematics. Existing …
-
Exact geometry algorithms for robotic motion planning
The current generation of robotic motion planning algorithms is dominated by derivatives of the PRM and RRT algorithms. These methods abstract away all geometric information about the underlying problem into a collision checker. While this approach yields simple and general purpose algorithms, it …
-
Learning Refinement Cost Estimators for Bilevel Planning
Bilevel planning is an effective approach for solving complex task and motion planning (TAMP) problems with continuous state and action spaces, that involves first searching for a high-level abstract plan and then refining it into a sequence of lowlevel actions. Although the low-level refinement …
-
Generalizable Robot Manipulation through Unified Perception, Policy Learning, and Planning
… across diverse goals, environments, and embodiments is a critical challenge in robotics research. While the availability of data and large-scale training has brought exciting progress in robotics manipulation, current methods often struggle with generalizing to unseen, unstructured …
-
Active Predicate Learning
Planning in robotics environments is difficult in part due to continuous state and action spaces. One approach to this challenge is to use bilevel planning, where decisionmaking occurs in multiple levels of abstraction. However, the efficacy and efficiency of bilevel planning relies on the …
-
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects
We present a framework for solving long-horizon planning problems involving manipulation of rigid objects that operates directly from a point-cloud observation, i.e. without prior object models. Our method plans in the space of object subgoals and frees the planner from reasoning about robot-object …
-
Learning Neuro-Symbolic Skills for Bilevel Planning
It is challenging for robots to solve tasks in environments with continuous state and action spaces, long horizons, and sparse feedback. Hierarchical approaches such as task and motion planning (TAMP) address this challenge, enabling efficient problem solving by decomposing decision-making into two …
-
Automated motion planning for robotic assembly of discrete architectural structures
… a promising technique for assembling non-standard configurations of building components at the scale of the built environment, complementing the earlier revolution in generative digital design. However, despite the advantages of dexterity and precision, the time investment in solving the …
-
Leveraging Mechanics for Multi-step Robotic Manipulation Planning
… perform complex, multi-step manipulation tasks, like chopping vegetables or wielding a wrench. Completing such tasks requires a robot to plan and execute long sequences of actions, where each action involves many connected, discrete and continuous choices that are critically impacted by …
-
Deformable Object Manipulation with a Tactile Reactive Gripper
… configuration spaces, frequent self-occlusion, and high model uncertainty, making global state estimation and predictive modeling unreliable. To address these challenges, we propose a perception-driven framework that combines global visual understanding with local tactile feedback. Rather than …
-
Reasoning over Hierarchical Abstractions for Long-Horizon Planning in Robotics
… hierarchical abstractions of their world, and planning within those representations. However, in reality, the types of abstractions robots are able to build are often poorly aligned with the planning problems they must solve, which limits how useful those abstractions can be in efficient …
Page 1 of 2