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Bernhard Thomaszewski

9 accepted papers

2025

Understanding the Impact of Modeling Abstractions on Motion Planning for Deformable Linear Objects

IROS 2025

Robotic manipulation of deformable objects remains challenging due to the high dimensional configuration space and complex dynamics. In this work we demonstrate how the abstraction level used for modeling deformable objects can significantly impact the difficulty of the motion planning problem. We s

Cited by 0SourceScholar
2024

Neural Modes: Self-supervised Learning of Nonlinear Modal Subspaces

CVPR 2024poster

We propose a self-supervised approach for learning physics-based subspaces for real-time simulation. Existing learning-based methods construct subspaces by approximating pre-defined simulation data in a purely geometric way. However this approach tends to produce high-energy configurations leads to…

Cited by 0SourcePDFScholar
2023

Computational Design of 3D-Printable Compliant Mechanisms with Bio-Inspired Sliding Joints

ICRA 2023poster

We propose a computational approach for designing fully-integrated compliant mechanisms with bio-inspired joints that are stabilized and actuated by elastic elements. Similar to human knees or finger phalanges, our mechanisms leverage sliding between pairs of contacting surfaces to generate complex…

Cited by 1SourceScholar
2023

Optimal Design of Flexible-Link Mechanisms With Desired Load-Displacement Profiles

RA-L 2023

Robot mechanisms that exploit compliance can perform complex tasks under uncertainty using simple control strategies, but it remains difficult to design mechanisms with a desired embodied intelligence. In this article, we propose an automated design technique that optimizes the desired load-displace

Cited by 4SourceScholar
2021

NTopo: Mesh-free Topology Optimization using Implicit Neural Representations

NeurIPS 2021poster

Recent advances in implicit neural representations show great promise when it comes to generating numerical solutions to partial differential equations. Compared to conventional alternatives, such representations employ parameterized neural networks to define, in a mesh-free manner, signals that are…

Cited by 86SourcePDFScholar
2021

Singularity-Aware Design Optimization for Multi-Degree-of-Freedom Spatial Linkages

RA-L 2021

We introduce a singularity-aware design optimization method for spatial multi-degree-of-freedom mechanical linkages. At the core of our approach is an adversarial sampling strategy, which actively detects singular configurations within the targeted operation range. The detection of singularities in

Cited by 4SourceScholar
2020

Computational Design of Balanced Open Link Planar Mechanisms with Counterweights from User Sketches

IROS 2020poster

We consider the design of under-actuated articulated mechanism that are able to maintain stable static balance. Our method augments an user-provided design with counter-weights whose mass and attachment locations are automatically computed. The optimized counterweights adjust the center of gravity s…

Cited by 3SourceScholar
2019

Computational Design of Statically Balanced Planar Spring Mechanisms

RA-L 2019

Statically balanced spring mechanisms are used in many applications that support our daily lives. However, creating new designs is a challenging problem since the designer has to simultaneously determine the right number of springs, their connectivity, attachment points, and other parameters. We pro

Cited by 16SourceScholar