403 research outputs found
Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot
We address the problem of enabling quadrupedal robots to perform precise
shooting skills in the real world using reinforcement learning. Developing
algorithms to enable a legged robot to shoot a soccer ball to a given target is
a challenging problem that combines robot motion control and planning into one
task. To solve this problem, we need to consider the dynamics limitation and
motion stability during the control of a dynamic legged robot. Moreover, we
need to consider motion planning to shoot the hard-to-model deformable ball
rolling on the ground with uncertain friction to a desired location. In this
paper, we propose a hierarchical framework that leverages deep reinforcement
learning to train (a) a robust motion control policy that can track arbitrary
motions and (b) a planning policy to decide the desired kicking motion to shoot
a soccer ball to a target. We deploy the proposed framework on an A1
quadrupedal robot and enable it to accurately shoot the ball to random targets
in the real world.Comment: Accepted to 2022 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS 2022
Hierarchical Reactive Control for Soccer Playing Humanoid Robots
What drives thousands of researchers worldwide to devote their creativity and energy t
Humanoid Robot Soccer Locomotion and Kick Dynamics: Open Loop Walking, Kicking and Morphing into Special Motions on the Nao Robot
Striker speed and accuracy in the RoboCup (SPL) international robot soccer league is becoming
increasingly important as the level of play rises. Competition around the ball is now decided in a
matter of seconds. Therefore, eliminating any wasted actions or motions is crucial when attempting to
kick the ball.
It is common to see a discontinuity between walking and kicking where a robot will return to an
initial pose in preparation for the kick action. In this thesis we explore the removal of this behaviour
by developing a transition gait that morphs the walk directly into the kick back swing pose. The
solution presented here is targeted towards the use of the Aldebaran walk for the Nao robot.
The solution we develop involves the design of a central pattern generator to allow for controlled
steps with realtime accuracy, and a phase locked loop method to synchronise with the Aldebaran walk
so that precise step length control can be activated when required. An open loop trajectory mapping
approach is taken to the walk that is stabilized statically through the use of a phase varying joint
holding torque technique. We also examine the basic princples of open loop walking, focussing on the
commonly overlooked frontal plane motion.
The act of kicking itself is explored both analytically and empirically, and solutions are provided
that are versatile and powerful. Included as an appendix, the broader matter of striker behaviour
(process of goal scoring) is reviewed and we present a velocity control algorithm that is very accurate
and efficient in terms of speed of execution
Project Pele: Humanoid Robotic Programming -A Study in Artificial Intelligence
In the ever changing world of technology, the humanoid robot has been a constant member of science fiction culture. Our project goal was to develop a humanoid robot capable of independently displaying effective soccer skills. We divided the tasks into two teams; one designed a ball kicking robot program while the other designed a path tracking robot program. After each group completed their four major objectives, we had created a superior program than its predecessors. Using our optimized code as a foundation, another group can further develop these robot programs to demonstrate even more humanlike soccer skills
Project Pele: Humanoid Robotic Programming A Study in Artificial Intelligence
In the ever changing world of technology, the humanoid robot has been a constant member of science fiction culture. Our project goal was to develop a humanoid robot capable of independently displaying effective soccer skills. We divided the tasks into two teams; one designed a ball kicking robot program while the other designed a path tracking robot program. After each group completed their four major objectives, we had created a superior program than its predecessors. Using our optimized code as a foundation, another group can further develop these robot programs to demonstrate even more humanlike soccer skills
Project Pele: Humanoid Robotic Programming - A Study in Artificial Intelligence
In the ever changing world of technology, the humanoid robot has been a constant member of science fiction culture. Our project goal was to develop a humanoid robot capable of independently displaying effective soccer skills. We divided the tasks into two teams; one designed a ball kicking robot program while the other designed a path tracking robot program. After each group completed their four major objectives, we had created a superior program than its predecessors. Using our optimized code as a foundation, another group can further develop these robot programs to demonstrate even more humanlike soccer skills
Penalty Kick of a Humanoid Robot by a Neural-Network-Based Active Embedded Vision System
[[abstract]]This paper realizes the humanoid robotic system to execute the penalty kick (PK) of the soccer game. The proposed system includes the following three subsystems: a humanoid robot (HR) with 22 degree-of-freedom, a soccer with different colors, and a soccer gate. In the beginning, the HR scans the soccer field to find the gate and the soccer, which are randomly distributed in a specific region in the front of the gate. If a command for the PK of the soccer with specific color is assigned, the HR will be navigated by an active embedded vision system (AEVS). After the HR reaches a planned position and posture, the PK of the HR will be executed. Two key important techniques are developed and integrated into the corresponding task. One is the modeling using multilayer neural network (MNN) for different view angles, the other is the visual navigation strategy for the PK of the HR. In addition, the error sensitivities in the pan and tilt directions of these four visible regions are analyzed and compared. The proposed strategy of the visual navigation includes the following two parts: (i) the switched visible regions are designed to navigate the HR to the planned position, and (ii) the posture revision of the HR in the neighborhood of the soccer in order to execute the PK. Finally, a sequence of experiments for the PK of the HR confirm the effectiveness and efficiency of the propose methodology.[[conferencetype]]國際[[conferencelocation]]Taipei, Taiwa
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