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Valentin N. Hartmann

7 accepted papers

2024

Effort Level Search in Infinite Completion Trees with Application to Task-and-Motion Planning

ICRA 2024poster

Solving a Task-and-Motion Planning (TAMP) problem can be represented as a sequential (meta-) decision process, where early decisions concern the skeleton (sequence of logic actions) and later decisions concern what to compute for such skeletons (e.g., action parameters, bounds, RRT paths, or full op…

Cited by 1SourceScholar
2024

iDb-RRT: Sampling-based Kinodynamic Motion Planning with Motion Primitives and Trajectory Optimization

IROS 2024poster

Rapidly-exploring Random Trees (RRT) and its variations have emerged as a robust and efficient tool for finding collision-free paths in robotic systems. However, adding dynamic constraints makes the motion planning problem significantly harder, as it requires solving two-value boundary problems (com…

Cited by 5SourceScholar
2023

Efficient Path Planning In Manipulation Planning Problems by Actively Reusing Validation Effort

IROS 2023poster

The path planning problems arising in manipulation planning and in task and motion planning settings are typically repetitive: the same manipulator moves in a space that only changes slightly. Despite this potential for reuse of information, few planners fully exploit the available information. To b…

Cited by 2SourceScholar
2022

Learning Robotic Manipulation of Natural Materials With Variable Properties for Construction Tasks

RA-L 2022

The introduction of robotics and machine learning to architectural construction is leading to more efficient construction practices. So far, robotic construction has largely been implemented on standardized materials, conducting simple, predictable, and repetitive tasks. We present a novel mobile ro

Cited by 12SourceScholar
2022

ST-RRT*: Asymptotically-Optimal Bidirectional Motion Planning through Space-Time

ICRA 2022poster

We present a motion planner for planning through space-time with dynamic obstacles, velocity constraints, and unknown arrival time. Our algorithm, Space-Time RRT*(ST-RRT*), is a probabilistically complete, bidirectional motion planning algorithm, which is asymptotically optimal with respect to the s…

Cited by 43SourceScholar
2021

Learning Efficient Constraint Graph Sampling for Robotic Sequential Manipulation

ICRA 2021poster

Efficient sampling from constraint manifolds, and thereby generating a diverse set of solutions for feasibility problems, is a fundamental challenge. We consider the case where a problem is factored, that is, the underlying nonlinear program is decomposed into differentiable equality and inequality…

Cited by 17SourceScholar
2020

Robust Task and Motion Planning for Long-Horizon Architectural Construction Planning

IROS 2020poster

Integrating robotic systems in architectural and construction processes is of core interest to increase the efficiency of the building industry. Automated planning for such systems enables design analysis tools and facilitates faster design iteration cycles for designers and engineers. However, gene…

Cited by 54SourceScholar