The Cambridge Companion to the Romantic Sublime

Interpretability in Contact-Rich Manipulation via Kinodynamic Images

Deep Neural Networks (NNs) have been widely utilized in contact-rich manipulation tasks to model the complicated contact dynamics. However, NN-based models are often difficult to decipher which can lead to seemingly inexplicable behaviors and unidentifiable failure cases. In this work, we address the interpretability of NN-based models by introducing the kinodynamic images. We propose a methodolog

ReForm: A Robot Learning Sandbox for Deformable Linear Object Manipulation

Recent advances in machine learning have triggered an enormous interest in using learning-based approaches for robot control and object manipulation. While the majority of existing algorithms are evaluated under the assumption that the involved bodies are rigid, a large number of practical applications contain deformable objects. In this work we focus on Deformable Linear Objects (DLOs) which can

Temporal Coupling of Dynamical Movement Primitives for Constrained Velocities and Accelerations

The framework of Dynamical Movement Primitives (DMPs) has become a popular method for trajectory generation in robotics. Most robotic systems are subject to saturation and/or kinematic constraints on motion variables, but DMPs do not inherently encode constraints and this may lead to poor tracking performance. Temporal coupling (online temporal scaling) of DMPs represents a possible way for handli

Task-Based Role Adaptation for Human-Robot Cooperative Object Handling

In this letter, we propose a task-based role allocation control scheme for the cooperative manipulation of a rigid-body object held jointly by a human and a robot. The task-based allocation scheme allows an assistive robot to take an active role when the task is known. To deal with the translation/rotation problem, we define rotation and translation as distinct parameterized tasks. The task that d

Human grasp position estimation for human–robot cooperative object manipulation

Amortized Variational Inference for Road Friction Estimation

Study protocol : The daicy trial—dual versus single-antibiotic impregnated cement in primary hemiarthroplasty for femoral neck fracture—a register-based cluster-randomized crossover-controlled trial

Background and purpose — Older patients with a displaced femoral neck fracture (FNF) are often treated with a cemented primary hemiarthroplasty (HA). The DAICY trial investigates whether high-dose dual-impregnated antibiotic-loaded cement (DIAC) including gentamicin and clindamycin can reduce the risk of periprosthetic joint infection (PJI) in comparison with low-dose single-impregnated gentamicin

Discrete Bimanual Manipulation for Wrench Balancing

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Comparison of CNN and LSTM for modeling virtual sensors in an engine

A Lyapunov-Based Approach to Exploit Asymmetries in Robotic Dual-Arm Task Resolution

Data-Driven Model Predictive Control for the Contact-Rich Task of Food Cutting

Asymmetric Dual-Arm Task Execution Using an Extended Relative Jacobian

Coordinated dual-arm manipulation tasks can be broadly characterized as possessing absolute and relative motion components. Relative motion tasks, in particular, are inherently redundant in the way they can be distributed between end-effectors. In this work, we analyse cooperative manipulation in terms of the asymmetric resolution of relative motion tasks. We discuss how existing approaches enable

Human-robot collaborative object transfer using human motion prediction based on Dynamic Movement Primitives

Human Motion Prediction in Human-Robot Handovers based on Dynamic Movement Primitives

Universal, Open Source, Myoelectric Interface for Assistive Devices

Cooperative Manipulation and Identification of a 2-DOF Articulated Object by a Dual-Arm Robot

Physical Human-Robot Interaction through a Jointly-held Object based on Kinesthetic Perception