Robotic Mechanisms and Dynamics

Latest papers

• Discrete Autoregressive Transformer for Generative Mechanism Synthesis

  Anar Nurizada, Anurag Purwar · 17 June 2026

  Planar path synthesis requires mechanisms whose coupler curves match a prescribed trajectory; the mapping from curve to linkage is inherently one-to-many across four-, six-, and eight-bar topologies. We address this design problem with simulation-grounded evaluation on a curated corpus of over one m…

• Bilevel Optimization of Synthetic Trajectories for Multi-Turn LLM Fine-Tuning

  Shresth Verma, Mauricio Tec, Cheol Woo Kim, Kai Wang, Milind Tambe · 26 May 2026

  While LLMs excel at single-turn generation, they struggle with long-horizon, multi-turn interactions. Offline reinforcement learning (RL) offers a scalable approach, yet its performance hinges on the availability and quality of multi-turn trajectory data. A common remedy is to augment training with …

• How Many Training Samples Are Needed for the Inverse Kinematics Solutions by Artificial Neural Networks

  Dong-Won Lim · 25 May 2026

  Inverse Kinematics (IK) plays a critical role in robotic motion planning and control. The IK solutions of a robot manipulator could be done by conventional ways such as geometric, algebraic, or Jacobian methods, which have drawbacks. The Artificial Neural Networks (ANNs) have become a promising alte…

• PiCa: Parameter-Efficient Fine-Tuning with Column Space Projection

  Junseo Hwang, Wonguk Cho, Taesup Kim · 21 April 2026

  Fine-tuning large foundation models is essential for building expert models tailored to specialized tasks and domains, but fully updating billions of parameters is computationally prohibitive. Reducing the number of trainable parameters using Parameter-Efficient Fine-Tuning (PEFT), such as Low-Rank …

• Geometry of Singular Foliations and Learning Manifolds in ReLU Networks via the Data Information Matrix

  Eliot Tron, Rita Fioresi · 13 March 2026

  Understanding how real data is distributed in high dimensional spaces is the key to many tasks in machine learning. We want to provide a natural geometric structure on the space of data employing a ReLU neural network trained as a classifier. Through the Data Information Matrix (DIM), a variation of…

• Multi-Objective Neural Network-Assisted Design Optimization of Soft Fin-Ray Fingers for Enhanced Grasping Performance

  Ali Ghanizadeh, Ali Ahmadi, Arash Bahrami · 17 February 2026

  The internal structure of the Fin-Ray fingers plays a significant role in their adaptability and grasping performance. However, modeling the grasp force and deformation behavior for design purposes is challenging. When the Fin-Ray finger becomes more rigid and capable of exerting higher forces, it b…

• IKDiffuser: a Diffusion-based Generative Inverse Kinematics Solver for Kinematic Trees

  Zeyu Zhang, Ziyuan Jiao · 15 January 2026

  Solving Inverse Kinematics (IK) for arbitrary kinematic trees presents significant challenges due to their high-dimensionality, redundancy, and complex inter-branch constraints. Conventional optimization-based solvers can be sensitive to initialization and suffer from local minima or conflicting gra…

• Certified Robust Invariant Polytope Training in Neural Controlled ODEs

  Akash Harapanahalli, Samuel Coogan · 12 November 2025

  We consider a nonlinear control system modeled as an ordinary differential equation subject to disturbance, with a state feedback controller parameterized as a feedforward neural network. We propose a framework for training controllers with certified robust forward invariant polytopes, where any tra…