113 citations · 294 across the 24 of their papers we have counts for
7 papers · 1 filter
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…
SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Visual SLAM
Bruno Bodin, Harry Wagstaff, Sajad Saeedi +9
SLAM is becoming a key component of robotics and augmented reality (AR) systems. While a large number of SLAM algorithms have been presented, there has been little effort to unify…
Comparative Design Space Exploration of Dense and Semi-Dense SLAM
M. Zeeshan Zia, Luigi Nardi, Andrew Jack +4
SLAM has matured significantly over the past few years, and is beginning to appear in serious commercial products. While new SLAM systems are being proposed at every conference, ev…
Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM
Luigi Nardi, Bruno Bodin, M. Zeeshan Zia +9
Real-time dense computer vision and SLAM offer great potential for a new level of scene modelling, tracking and real environmental interaction for many types of robot, but their hi…