Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots) and dynamic (moving robots) obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams

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

Comparing Computing Platforms for Deep Learning on a Humanoid Robot

The goal of this study is to test two different computing platforms with respect to their suitability for running deep networks as part of a humanoid robot software system. One of the platforms is the CPU-centered Intel NUC7i7BNH and the other is a NVIDIA Jetson TX2 system that puts more emphasis on GPU processing. The experiments addressed a number of benchmarking tasks including pedestrian detection using deep neural networks. Some of the results were unexpected but demonstrate that platforms exhibit both advantages and disadvantages when taking computational performance and electrical power requirements of such a system into account.Comment: 12 pages, 5 figure

Utilising human performance criteria and computer simulation to design a martial arts kicking robot with increased biofidelity

The rules and regulations of Taekwondo stipulate how the sport must be played and the necessary personal protective equipment. As such, personal protective equipment performance under controlled rigid drop-tests is also outlined. Unfortunately, these impacts do not replicate human loading effectively, making conclusions about their performance unknown. However, it may be possible to use human kinematic data to improve the biofidelity of current impactors, including a current single-segment martial arts kicking robot. Five martial artists performed a series of roundhouse kicks while reflective markers on the kicking leg and pelvis were used to track hip, knee, ankle and foot positions. Using specific single-segment martial arts kicking robot robot parameters, computer simulation was used to model a singlesegment martial arts kicking robot performance (1-SM) and to form a multi-segment, multi-joint model to match human kinematic data (3-SM). The 3-SM was found to produce similar kinematics to human performance while reducing the overall effective mass at impact, motor torque and stress concentration magnitudes in the leg when compared to the 1-SM. This study suggested that human performances could be used to improve current mechanical testing techniques without introducing much complexity to improve the external validity of protective equipment evaluation testing

Individual and coordinated decision for the CAMBADA team

Mestrado em Engenharia de Computadores e TelemáticaA coordenação em sistemas multi-robô é um aspecto crucial no futebol robótico. A maneira como cada equipa coordena cada um dos seus robôs em acções cooperativas define a base da sua estratégia. Este trabalho tem como foco o desenvolvimento da coordenação e estratégia da equipa CAMBADA. CAMBADA é a equipa de futebol robótico da modalidade RoboCup Middle Size League da Universidade de Aveiro. Foi desenvolvida pelo grupo ATRI, pertencente µa unidade de investigação IEETA. O presente trabalho baseia-se em trabalho desenvolvido anteriormente, tentando melhorar o desempenho da equipa. Cada robô da equipa CAMBADA é um agente independente e autónomo capaz de coordenar as suas acções com os colegas de equipa através da comunicação e da partilha de informação. O comportamento de cada robô deverá ser integrado na estratégia global da equipa, resultando assim em acções cooperativas de todos os robôs. Isto é conseguido através do uso de papeis(roles) e comportamentos(behaviours) que definem a atitude de cada robô e as acções que daí resultam. Novos papeis foram desenvolvidos para complementar a estratégia de equipa, e alguns dos papeis existentes foram melhorados. Também foram efectuadas melhorias em alguns dos comportamentos existentes. É efectu- ada a descrição de cada um destes papeis e comportamentos, assim como as alterações efectuadas. O trabalho desenvolvido foi testado nas competições do Robótica 2008 (o desenvolvimento não estava ainda concluído) e por fim nas competições do RoboCup'2008. A participação da equipa no RoboCup'2008 é analisada e discutida. A equipa consagrou-se campeã mundial, vencendo a competição da Middle Size League do RoboCup'2008 em Suzhou, China. ABSTRACT: Multi-robot coordination is one crucial aspect in robotic soccer. The way each team coordinates its individual robots into cooperative global actions define the foundation of its strategy. CAMBADA is the RoboCup Middle Size League robotic soccer team of the University of Aveiro. It was created by the ATRI group, part of the IEETA research unit. This work is focused on coordination and strategy development for the CAMBADA team. It is built upon previous work and tries to improve the team performance further. In CAMBADA each robot is an independent agent, it coordinates its actions with its teammates through communication and information exchange. The resulting behaviour of the individual robot should be integrated into the global team strategy, thus resulting in cooperative actions by all the robots. This is done by the use of roles and behaviours that define each robot attitude in the field and resulting individual actions. In this work, new roles were created to add to the team strategy and some of the previous existing roles were improved. Some of the existing behaviours were also improved to better fit the desired goals. Each role and behaviour is described as well as the changes made. The resulting work was put to test in the portuguese Robotica 2008 competition (while still in progress) and finally in the RoboCup'2008 world competitions. The performance of the team in the latter is analysed and discussed. The team achieved the 1st place in the RoboCup'2008 MSL world competitions

IMPLEMENTATION OF A LOCALIZATION-ORIENTED HRI FOR WALKING ROBOTS IN THE ROBOCUP ENVIRONMENT

This paper presents the design and implementation of a human–robot interface capable of evaluating robot localization performance and maintaining full control of robot behaviors in the RoboCup domain. The system consists of legged robots, behavior modules, an overhead visual tracking system, and a graphic user interface. A human–robot communication framework is designed for executing cooperative and competitive processing tasks between users and robots by using object oriented and modularized software architecture, operability, and functionality. Some experimental results are presented to show the performance of the proposed system based on simulated and real-time information. </jats:p

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