Related papers: Cyrus2D base: Source Code Base for RoboCup 2D Socc…
Field detection in team sports is an essential task in sports video analysis. However, collecting large-scale and diverse real-world datasets for training detection models is often cost and time-consuming. Synthetic datasets, which allow…
Scientific competitions are crucial in the field of service robotics. They foster knowledge exchange and allow teams to test their research in unstandardized scenarios and compare result. Such is the case of RoboCup@Home. However, keeping…
In soccer video analysis, player detection is essential for identifying key events and reconstructing tactical positions. The presence of numerous players and frequent occlusions, combined with copyright restrictions, severely restricts the…
Reinforcement learning algorithms have performed well in playing challenging board and video games. More and more studies focus on improving the generalisation ability of reinforcement learning algorithms. The General Video Game AI Learning…
RoboCup SSL is an excellent platform for researching artificial intelligence and robotics. The dribbling system is an essential issue, which is the main part for completing advanced soccer skills such as trapping and dribbling. In this…
This paper presents a technique to train a robot to perform kick-motion in AI soccer by using reinforcement learning (RL). In RL, an agent interacts with an environment and learns to choose an action in a state at each step. When training…
The need for autonomous robot systems in both the service and the industrial domain is larger than ever. In the latter, the transition to small batches or even "batch size 1" in production created a need for robot control system…
Robot sports, characterized by well-defined objectives, explicit rules, and dynamic interactions, present ideal scenarios for demonstrating embodied intelligence. In this paper, we present VolleyBots, a novel robot sports testbed where…
We introduce Pixels2Play-0.1 (P2P0.1), a foundation model that learns to play a wide range of 3D video games with recognizable human-like behavior. Motivated by emerging consumer and developer use cases - AI teammates, controllable NPCs,…
Humanoid soccer dribbling is a highly challenging task that demands dexterous ball manipulation while maintaining dynamic balance. Traditional rule-based methods often struggle to achieve accurate ball control due to their reliance on fixed…
We participated in the RoboCup 2018 competition in Montreal with our newly developed BoldBot based on the Darwin-OP and mostly self-printed custom parts. This paper is about the lessons learnt from that competition and further developments…
Automated game testing is important for verifying game functionality, but it remains a costly and time-consuming process. Manual testing often misses edge cases, and current automated methods struggle to provide full code coverage. Prior…
In the RoboCup Small Size League (SSL), teams are encouraged to propose solutions for executing basic soccer tasks inside the SSL field using only embedded sensing information. Thus, this work proposes an embedded monocular vision approach…
There are many AI tasks involving multiple interacting agents where agents should learn to cooperate and collaborate to effectively perform the task. Here we develop and evaluate various multi-agent protocols to train agents to collaborate…
Although many competitions have been held on dialogue systems in the past, no competition has been organized specifically for dialogue with humanoid robots. As the first such attempt in the world, we held a dialogue robot competition in…
Simulation is crucial in real-world robotics, offering safe, scalable, and efficient environments for developing applications, ranging from humanoid robots to autonomous vehicles and drones. While the Robot Operating System (ROS) has been…
We apply multi-agent deep reinforcement learning (RL) to train end-to-end robot soccer policies with fully onboard computation and sensing via egocentric RGB vision. This setting reflects many challenges of real-world robotics, including…
In this work, we report on strategies and results of our initial approach for modernization of Titan2D code. Titan2D is a geophysical mass flow simulation code designed for modeling of volcanic flows, debris avalanches and landslides over a…
The supercomputing platforms available for high performance computing based research evolve at a great rate. However, this rapid development of novel technologies requires constant adaptations and optimizations of the existing codes for…
ZJUNlict became the Small Size League Champion of RoboCup 2019 with 6 victories and 1 tie for their 7 games. The overwhelming ability of ball-handling and passing allows ZJUNlict to greatly threaten its opponent and almost kept its goal…