35 citations · 86 across the 14 of their papers we have counts for
14 papers
A Multimodal Data Set of Human Handovers with Design Implications for Human-Robot Handovers
Parag Khanna, Mårten Björkman, Christian Smith
Handovers are basic yet sophisticated motor tasks performed seamlessly by humans. They are among the most common activities in our daily lives and social environments. This makes m…
User Study Exploring the Role of Explanation of Failures by Robots in Human Robot Collaboration Tasks
Parag Khanna, Elmira Yadollahi, Mårten Björkman +2
Despite great advances in what robots can do, they still experience failures in human-robot collaborative tasks due to high randomness in unstructured human environments. Moreover,…
Data-driven Grip Force Variation in Robot-Human Handovers
Parag Khanna, Mårten Björkman, Christian Smith
Handovers frequently occur in our social environments, making it imperative for a collaborative robotic system to master the skill of handover. In this work, we aim to investigate…
A Framework for Learning Behavior Trees in Collaborative Robotic Applications
Matteo Iovino, Jonathan Styrud, Pietro Falco +1
In modern industrial collaborative robotic applications, it is desirable to create robot programs automatically, intuitively, and time-efficiently. Moreover, robots need to be cont…
Behavior Trees for Robust Task Level Control in Robotic Applications
Matteo Iovino, Christian Smith
Behavior Trees are a task switching policy representation that can grant reactiveness and fault tolerance. Moreover, because of their structure and modularity, a variety of methods…
On the programming effort required to generate Behavior Trees and Finite State Machines for robotic applications
Matteo Iovino, Julian Förster, Pietro Falco +3
In this paper we provide a practical demonstration of how the modularity in a Behavior Tree (BT) decreases the effort in programming a robot task when compared to a Finite State Ma…
Interactive Disambiguation for Behavior Tree Execution
Matteo Iovino, Fethiye Irmak Doğan, Iolanda Leite +1
In recent years, robots are used in an increasing variety of tasks, especially by small- and medium- sized enterprises. These tasks are usually fast-changing, they have a collabora…
Combining Context Awareness and Planning to Learn Behavior Trees from Demonstration
Oscar Gustavsson, Matteo Iovino, Jonathan Styrud +1
Fast changing tasks in unpredictable, collaborative environments are typical for medium-small companies, where robotised applications are increasing. Thus, robot programs should be…
Combining Planning and Learning of Behavior Trees for Robotic Assembly
Jonathan Styrud, Matteo Iovino, Mikael Norrlöf +2
Industrial robots can solve very complex tasks in controlled environments, but modern applications require robots able to operate in unpredictable surroundings as well. An increasi…
Learning Behavior Trees with Genetic Programming in Unpredictable Environments
Matteo Iovino, Jonathan Styrud, Pietro Falco +1
Modern industrial applications require robots to be able to operate in unpredictable environments, and programs to be created with a minimal effort, as there may be frequent change…
A Survey of Behavior Trees in Robotics and AI
Matteo Iovino, Edvards Scukins, Jonathan Styrud +2
Behavior Trees (BTs) were invented as a tool to enable modular AI in computer games, but have received an increasing amount of attention in the robotics community in the last decad…
Dual-Arm In-Hand Manipulation and Regrasping Using Dexterous Manipulation Graphs
Silvia Cruciani, Kaiyu Hang, Christian Smith +1
This work focuses on the problem of in-hand manipulation and regrasping of objects with parallel grippers. We propose Dexterous Manipulation Graph (DMG) as a representation on whic…
Dexterous Manipulation Graphs
Silvia Cruciani, Christian Smith, Danica Kragic +1
We propose the Dexterous Manipulation Graph as a tool to address in-hand manipulation and reposition an object inside a robot's end-effector. This graph is used to plan a sequence…
Reinforcement Learning for Pivoting Task
Rika Antonova, Silvia Cruciani, Christian Smith +1
In this work we propose an approach to learn a robust policy for solving the pivoting task. Recently, several model-free continuous control algorithms were shown to learn successfu…