3 citations · 6 across the 31 of their papers we have counts for
33 papers
Identifiable Decomposition of Submovements in Human Hand Trajectories
Adrian Prados, James Hermus, Ramon Barber +1
Voluntary movements have long been hypothesised to be comprised of discrete primitives called submovements, as a descriptive model of human motor behaviour. However, existing metho…
Ergodic Control and Controlled Diffusion for Robot Learning: Review and Tutorial
Max Muchen Sun, Cem Bilaloglu, Ananya Rao +6
Diffusion learning leverages the statistical mechanism of diffusion processes for learning, reasoning, and inferring complex distributions from data. Recent advances in diffusion l…
Spline Policy: A Structured Representation for Robot Policies
Mengze Tian, Yiming Li, Sichao Liu +2
Modern imitation-learning policies for robot manipulation often represent actions as fixed-resolution action chunks, which are simple and effective but expose limited geometric and…
Physics-Informed Eikonal Caging for Whole-Arm Manipulation Planning
Yan Zhang, Yiming Li, Yifei Dong +2
Planning contact-rich whole-arm manipulation is challenging because interactions that involve extended robot geometry give rise to complex contact dynamics that are difficult to mo…
Ergodic Imitation for Adaptive Exploration around Demonstrations
Ziyi Xu, Cem Bilaloglu, Yiming Li +1
In robotics, a common challenge in imitation learning is the mismatch between training and deployment conditions, caused, for example, by environmental changes or imperfect observa…
Fast and Safe Trajectory Optimization for Mobile Manipulators With Neural Configuration Space Distance Field
Yulin Li, Zhiyuan Song, Yiming Li +8
Mobile manipulators promise agile, long-horizon behavior by coordinating base and arm motion, yet whole-body trajectory optimization in cluttered, confined spaces remains difficult…
Object-centric Task Representation and Transfer using Diffused Orientation Fields
Cem Bilaloglu, Tobias Löw, Sylvain Calinon
Curved objects pose a fundamental challenge for skill transfer in robotics: unlike planar surfaces, they do not admit a global reference frame. As a result, task-relevant direction…
Geometry-aware Policy Imitation
Yiming Li, Nael Darwiche, Amirreza Razmjoo +4
We propose a Geometry-aware Policy Imitation (GPI) approach that rethinks imitation learning by treating demonstrations as geometric curves rather than collections of state-action…
Cooperative Task Spaces for Multi-Arm Manipulation Control based on Similarity Transformations
Tobias Löw, Cem Bilaloglu, Sylvain Calinon
Many tasks in human environments require collaborative behavior between multiple kinematic chains, either to provide additional support for carrying big and bulky objects or to ena…
Monte Carlo Tree Search with Tensor Factorization for Optimization Problems in Robotics
Teng Xue, Yan Zhang, Amirreza Razmjoo +1
Many robotic tasks, such as inverse kinematics, motion planning, and contact-rich manipulation, can be formulated as optimization problems. Solving these problems requires addressi…
Efficient and Real-Time Motion Planning for Robotics Using Projection-Based Optimization
Xuemin Chi, Hakan Girgin, Tobias Löw +6
Generating motions for robots interacting with objects of various shapes is a complex challenge, further complicated by the robot geometry and multiple desired behaviors. While cur…
Robustness-Aware Tool Selection and Manipulation Planning with Learned Energy-Informed Guidance
Yifei Dong, Yan Zhang, Sylvain Calinon +1
Humans subconsciously choose robust ways of selecting and using tools, for example, choosing a ladle over a flat spatula to serve meatballs. However, robustness under external dist…
A Smooth Analytical Formulation of Collision Detection and Rigid Body Dynamics With Contact
Onur Beker, Nico Gürtler, Ji Shi +4
Generating intelligent robot behavior in contact-rich settings is a research problem where zeroth-order methods currently prevail. A major contributor to the success of such method…
From Movement Primitives to Distance Fields to Dynamical Systems
Yiming Li, Sylvain Calinon
Developing autonomous robots capable of learning and reproducing complex motions from demonstrations remains a fundamental challenge in robotics. On the one hand, movement primitiv…
CCDP: Composition of Conditional Diffusion Policies with Guided Sampling
Amirreza Razmjoo, Sylvain Calinon, Michael Gienger +1
Imitation Learning offers a promising approach to learn directly from data without requiring explicit models, simulations, or detailed task definitions. During inference, actions a…
Safe Dynamic Motion Generation in Configuration Space Using Differentiable Distance Fields
Xuemin Chi, Yiming Li, Jihao Huang +3
Generating collision-free motions in dynamic environments is a challenging problem for high-dimensional robotics, particularly under real-time constraints. Control Barrier Function…
Sampling-Based Constrained Motion Planning with Products of Experts
Amirreza Razmjoo, Teng Xue, Suhan Shetty +1
We present a novel approach to enhance the performance of sampling-based Model Predictive Control (MPC) in constrained optimization by leveraging products of experts. Our methodolo…
Robust Contact-rich Manipulation through Implicit Motor Adaptation
Teng Xue, Amirreza Razmjoo, Suhan Shetty +1
Contact-rich manipulation plays an important role in daily human activities. However, uncertain physical parameters often pose significant challenges for both planning and control.…
A Riemannian Take on Distance Fields and Geodesic Flows in Robotics
Yiming Li, Jiacheng Qiu, Sylvain Calinon
Distance functions are crucial in robotics for representing spatial relationships between a robot and its environment. They provide an implicit, continuous, and differentiable repr…
Diffusion-based Virtual Fixtures
Cem Bilaloglu, Tobias Löw, Sylvain Calinon
Virtual fixtures assist human operators in teleoperation settings by constraining their actions. This extended abstract introduces a novel virtual fixture formulation \emph{on surf…
Robust Manipulation Primitive Learning via Domain Contraction
Teng Xue, Amirreza Razmjoo, Suhan Shetty +1
Contact-rich manipulation plays an important role in human daily activities, but uncertain parameters pose significant challenges for robots to achieve comparable performance throu…
Learn2Decompose: Learning Problem Decomposition for Efficient Sequential Multi-object Manipulation Planning
Yan Zhang, Teng Xue, Amirreza Razmjoo +1
We present an efficient task and motion replanning approach for sequential multi-object manipulation in dynamic environments. Conventional Task And Motion Planning (TAMP) solvers e…
Configuration Space Distance Fields for Manipulation Planning
Yiming Li, Xuemin Chi, Amirreza Razmjoo +1
The signed distance field is a popular implicit shape representation in robotics, providing geometric information about objects and obstacles in a form that can easily be combined…
Logic-Skill Programming: An Optimization-based Approach to Sequential Skill Planning
Teng Xue, Amirreza Razmjoo, Suhan Shetty +1
Recent advances in robot skill learning have unlocked the potential to construct task-agnostic skill libraries, facilitating the seamless sequencing of multiple simple manipulation…