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This paper presents the new Deep Reinforcement Learning (DRL) library RL-X and its application to the RoboCup Soccer Simulation 3D League and classic DRL benchmarks. RL-X provides a flexible and easy-to-extend codebase with self-contained single directory algorithms. Through the fast JAX-based implementations, RL-X can reach up to 4.5x speedups compared to well-known frameworks like Stable-Baselines3.
This paper describes the magmaOffenburg 3D simulation team trying to qualify for RoboCup 2013. While last year’s TDP focused on different ways how robot behavior can be defined in the magmaOffenburg framework this year we focus on how we statistically evaluate new features on distributed systems. We also show some results gained through such analysis.
This paper describes the magmaOffenburg 3D simulation team trying to qualify for RoboCup 2012. While last year’s TDP focused on the tool set created for 3D simulation and the support for heterogeneous robot models, this year we focus on the different ways how robot behavior can be defined in the magmaOffenburg framework and how those behaviors can be improved by learning.
This paper describes the magmaOffenburg 3D simulation team trying to qualify for RoboCup 2011. While last year’s TDP focused on the tool set created for 3D simulation in this year we describe the further improvement in this tools as well as some new features we implemented focusing on heterogeneous robot models which seem to be used in RoboCup 2012.
An additional tool was written to simply generate situation-dependent strategies. Furthermore some tools, described last year, are now integrated in one single GUI to easy things up.
This paper describes the magmaOffenburg 3D simulation team trying to qualify for RoboCup 2010. While last year’s TDP focused on decisions making using extended behavior networks and on its software architecture and implementation in this year we describe the tool set that was created for RoboCup 3D. It contians a GUI for agent- and world state visualization, for evaluation of localization algorithms and benchmarks in general, a visual editor for Extended Behavior Networks creation and debugging, a live movement tool to interact with the joints and finally a tool for editing behavior motor files.
This paper describes the magmaOffenburg 3D simulation team trying to qualify for RoboCup 2009. It focuses on two distinctive features of the team: decisions making using extended behavior networks and its software architecture and implementation in Java to open the simulation for the Java community.
Team description papers of magmaOffenburg are incremental in the sense that each year we address a different topic of our team and the tools around our team. In this year’s team description paper we focus on the architecture of the software. It is a main factor for being able to keep the code maintainable even after 15 years of development. We also describe how we make sure that the code follows this architecture.
Autonomous humanoid robots require light weight, high torque and high speed actuators to be able to walk and run. For conventional gears with a fixed gear ratio the product of torque and velocity is constant. On the other hand desired motions require maximum torque and speed. In this paper it is shown that with a variable gear ratio it is possible to vary the relation between torque and velocity. This is achieved by introducing systems of rods and levers to move the joints of our humanoid robot ”Sweaty II”. On the basis of a variable gear ratio low speed and high torque can be achieved for those joint angles, which require this motion mode, whereas high speed and low torque can be realized for those joint angles, where it is favorable for the desired motion.
Existing approaches solving multi-vehicle pickup and delivery problems with soft time windows typically use common benchmark sets to verify their performance. However, there is a gap from these benchmark sets to real world problems with respect to instance size and problem complexity. In this paper we show that a combination of existing approaches together with improved heuristics is able to deal with the instance sizes and complexity of real world problems. The cost savings potential of the heuristics is compared to human dispatching plans generated from the data of a European carrier.
Sweaty has already participated several times in RoboCup soccer competitions (Adult Size). Now the work is focused coordinating the play of two robots. Moreover, we are working on stabilizing the gait by adding additional sensor information. An ongoing work is the optimization of the control strategy by balancing between impedance and position control. By minimizing the jerk, gait and overall gameplay should improve significantly.
Sweaty has already participated several times in RoboCup soccer competitions (Adult Size). Now the work is focused on stabilizing the gait. Moreover, we would like to overcome the constraints of a ZMP-algorithm that has a horizontal footplate as precondition for the simplification of the equations. In addition we would like to switch between impedance and position control with a fuzzy-like algorithm that might help to minimize jerks when Sweaty’s feet touch the ground.