19 citations · 23 across the 12 of their papers we have counts for
12 papers
Quest2ROS2: A ROS 2 Framework for Bi-manual VR Teleoperation
Jialong Li, Zhenguo Wang, Tianci Wang +2
Quest2ROS2 is an open-source ROS2 framework for bi-manual teleoperation designed to scale robot data collection. Extending Quest2ROS, it overcomes workspace limitations via relativ…
3D Hand-Eye Calibration for Collaborative Robot Arm: Look at Robot Base Once
Leihui Li, Lixuepiao Wan, Volker Krueger +1
Hand-eye calibration is a common problem in the field of collaborative robotics, involving the determination of the transformation matrix between the visual sensor and the robot fl…
A Unified Framework for Real-Time Failure Handling in Robotics Using Vision-Language Models, Reactive Planner and Behavior Trees
Faseeh Ahmad, Hashim Ismail, Jonathan Styrud +2
Robotic systems often face execution failures due to unexpected obstacles, sensor errors, or environmental changes. Traditional failure recovery methods rely on predefined strategi…
Addressing Failures in Robotics using Vision-Based Language Models (VLMs) and Behavior Trees (BT)
Faseeh Ahmad, Jonathan Styrud, Volker Krueger
In this paper, we propose an approach that combines Vision Language Models (VLMs) and Behavior Trees (BTs) to address failures in robotics. Current robotic systems can handle known…
Adaptable Recovery Behaviors in Robotics: A Behavior Trees and Motion Generators(BTMG) Approach for Failure Management
Faseeh Ahmad, Matthias Mayr, Sulthan Suresh-Fazeela +1
In dynamic operational environments, particularly in collaborative robotics, the inevitability of failures necessitates robust and adaptable recovery strategies. Traditional automa…
Flexible and Adaptive Manufacturing by Complementing Knowledge Representation, Reasoning and Planning with Reinforcement Learning
Matthias Mayr, Faseeh Ahmad, Volker Krueger
This paper describes a novel approach to adaptive manufacturing in the context of small batch production and customization. It focuses on integrating task-level planning and reason…
BeBOP -- Combining Reactive Planning and Bayesian Optimization to Solve Robotic Manipulation Tasks
Jonathan Styrud, Matthias Mayr, Erik Hellsten +2
Robotic systems for manipulation tasks are increasingly expected to be easy to configure for new tasks. While in the past, robot programs were often written statically and tuned ma…
Learning Actions and Control of Focus of Attention with a Log-Polar-like Sensor
Robin Göransson, Volker Krueger
With the long-term goal of reducing the image processing time on an autonomous mobile robot in mind we explore in this paper the use of log-polar like image data with gaze control.…
Combining Planning, Reasoning and Reinforcement Learning to solve Industrial Robot Tasks
Matthias Mayr, Faseeh Ahmad, Konstantinos Chatzilygeroudis +2
One of today's goals for industrial robot systems is to allow fast and easy provisioning for new tasks. Skill-based systems that use planning and knowledge representation have long…
Learning Skill-based Industrial Robot Tasks with User Priors
Matthias Mayr, Carl Hvarfner, Konstantinos Chatzilygeroudis +2
Robot skills systems are meant to reduce robot setup time for new manufacturing tasks. Yet, for dexterous, contact-rich tasks, it is often difficult to find the right skill paramet…
Skill-based Multi-objective Reinforcement Learning of Industrial Robot Tasks with Planning and Knowledge Integration
Matthias Mayr, Faseeh Ahmad, Konstantinos Chatzilygeroudis +2
In modern industrial settings with small batch sizes it should be easy to set up a robot system for a new task. Strategies exist, e.g. the use of skills, but when it comes to handl…
Learning of Parameters in Behavior Trees for Movement Skills
Matthias Mayr, Konstantinos Chatzilygeroudis, Faseeh Ahmad +2
Reinforcement Learning (RL) is a powerful mathematical framework that allows robots to learn complex skills by trial-and-error. Despite numerous successes in many applications, RL…