Artur Pereira

CAMBADA Soccer Team: from Robot Architecture to Multiagent Coordination

Robotic soccer is nowadays a popular research domain in the area of multi-robot systems. RoboCup is an international joint project to promote research in artificial intelligence, robotics and related fields. RoboCup chose soccer as the main problem aiming at innovations to be applied for socially relevant problems. It includes several competition leagues, each one with a specific emphasis, some only at software level, others at both hardware and software, with single or multiple agents, cooperative and competitive. In the context of RoboCup, the Middle Size League (MSL) is one of the most challenging. In this league, each team is composed of up to 5 robots with a maximum size of 50cm× 50cm, 80cm height and a maximumweight of 40Kg, playing in a field of 18m× 12m. The rules of the game are similar to the official FIFA rules, with minor changes required to adapt them for the playing robots CAMBADA, Cooperative Autonomous Mobile roBots with Advanced Distributed Architecture, is the MSL Soccer team from the University of Aveiro. The project started in 2003, coordinated by the Transverse Activity on Intelligent Robotics group of the Institute of Electronic and Telematic Engineering of Aveiro (IEETA). This project involves people working on several areas for building the mechanical structure of the robot, its hardware architecture and controllers (Almeida et al., 2002; Azevedo et al., 2007) and the software development in areas such as image analysis and processing (Caleiro et al., 2007; Cunha et al., 2007; Martins et al., 2008; Neves et al., 2007; 2008), sensor and information fusion (Silva et al., 2008; 2009), reasoning and control (Lau et al., 2008), cooperative sensing approach based on a Real-Time Database (Almeida et al., 2004), communications among robots (Santos et al., 2009; 2007) and the development of an efficient basestation. The main contribution of this chapter is to present the new advances in the areas described above involving the development of an MSL team of soccer robots, taking the example of the CAMBADA team that won the RoboCup 2008 and attained the third place in the last edition of the MSL tournament at RoboCup 2009. CAMBADA also won the last three editions

Online SLAM Based on a Fast Scan-Matching Algorithm

This paper presents a scan-matching approach for online simultaneous localization and mapping. This approach combines a fast and efficient scan-matching algorithm for localization with dynamic and approximate likelihood fields to incrementally build a map. The achievable results of the approach are evaluated using an objective benchmark designed to compare SLAM solutions that use different methods. The result is a fast online SLAM approach suitable for real-time operations.

MULTI-AGENT DEBUGGING AND MONITORING FRAMEWORK

Abstract In this paper we present a framework developed for the CAMBADA Middle-sized league robotic team, which allows human developers to better understand the robots actions during a game. Robotic soccer teams are in their nature dynamic multi-process and multi-agent systems, and knowing what is happening in all processes running on the agents at the same time is a hard task. To accomplish this task we developed a framework to create log files, one per process, and to interlace them later. The logs represent robots knowledge. The framework allows the synchronization and visualization of logs and videos. Videos give the actual real behaviors. This will allow us to understand the robots reasoning. A GUI utility to navigate and search inside log files was also developed.

A Skill-Based Architecture for Pick and Place Manipulation Tasks

Robots can play a significant role in product customization but they should leave a repetitive, low intelligence paradigm and be able to operate in unstructured environments and take decisions during the execution of the task. The EuRoC research project addresses this issue by posing as a competition to motivate researchers to present their solution to the problem. The first stage is a simulation competition where Pick & Place type of tasks are the goal and planning, perception and manipulation are the problems. This paper presents a skill-based architecture that enables a simulated moving manipulator to solve these tasks. The heuristics that were used to solve specific tasks are also presented. Using computer vision methods and the definition of a set of manipulation skills, an intelligent agent is able to solve them autonomously. The work developed in this project was used in the simulation competition of EuRoC project by team IRIS and enabled them to reach the \(5^{\mathrm {th}}\) rank.

Rich and robust human-robot interaction on gesture recognition for assembly tasks

The adoption of robotics technology has the potential to advance quality, efficiency and safety for manufacturing enterprises, in particular small and medium-sized enterprises. This paper presents a human-robot interaction (HRI) system that enables a robot to receive commands, provide information to a human teammate and ask them a favor. In order to build a robust HRI system based on gesture recognition, three key issues are addressed: richness, multiple feature fusion and failure verification. The developed system has been tested and validated in a realistic lab with a real mobile manipulator and a human teammate to solve a puzzle game.

Skill-based anytime agent architecture for logistics and manipulation tasks: EuRoC Challenge 2, Stage II - Realistic Labs: Benchmarking

Nowadays, the increase of robotic technology application to industry scenarios is notorious. Proposals for new effective solutions are in continuous development once industry needs a constantly improvement in time as well as in production quality and efficiency. The EuRoC research project proposes a scientific competition in which research and industry manufacturers joint teams are encouraged to develop and test solutions that can solve several issues as well as be useful in manufacturing improvement. This paper presents the TIMAIRIS architecture and approach used in the Challenge 2 - Stage II - Benchmarking phase, namely regarding the perception, manipulation and planning strategy that was applied to achieve the tasks objectives. The used approach proved to be quite robust and efficient, which allowed us to rank first in the Benchmarking phase.

A Scan Matching Approach to SLAM with a Dynamic Likelihood Field

This paper presents a fast scan matching approach to online SLAM supported by a dynamic likelihood field. The dynamic likelihood field plays a central role in the approach, as it avoids the necessity to establish direct correspondences, it is the connection link between scan matching and the online SLAM and it has a low computational complexity. Scan matching is formulated as a non-linear least squares problem and solved by the Gauss-Newton method. Furthermore, to reduce the influences of outliers during optimization, a loss function is introduced. The proposed solution was evaluated using an objective benchmark designed to compare SLAM solutions and its execution times were also analyzed. It shows to be a fast and accurate online SLAM approach, suitable for real-time operation.

How to Select a Suitable Action against Strong Pushes in Adult-Size Humanoid Robot: Learning from Past Experiences

Avoiding a fall after strong collisions between two players is an important capability for an adult-size humanoid robot. Particularly in the RoboCup competitions, matches are really competitive and collisions between players are occurred frequently. In the adult-size humanoid league, robots are tall and heavy. Whenever robots contact each other during moving, several unpredicted non-linear forces are entered to the robots. As a consequence, the stability of robots goes out of control and they fall down. In order to maintain and recover balance of an adult-size humanoid robot against external disturbances, a Neural Network is used for learning from past experiments to reduce the effect of disturbances forces by providing proper step sizes and joint angles to the robot. In our approach, the robots controller is learned using several empirical experiments and tested on a real adult-size humanoid robot namely Ariana from BehRobot humanoid team. Experiments demonstrate after receiving strong pushes during walking, Ariana can efficiently recover its stability in the real environment.

A reliable model-based walking engine with push recovery capability

Bipedal humanoid robots have complex dynamics and they are intrinsically unstable. Although, bipedal robots have a similar kinematic architecture to a human and they are the most appropriate type of robots to operate in human environments, developing a humanoid robot that has robust is a difficult task. This paper proposes an omnidirectional walking engine that takes into account the push recovery strategies. The walking engine has a hierarchical structure and tries to fade the complexities of the dynamic walking. In addition, it can adapt to another platform with few changes. We enhanced the Linear Inverted Pendulum Plus Flywheel Model to release the height constraint of the center of mass. This enhancement allows a more human-like motion and provides more stable walking. The proposed walking engine has been successfully tested on a real humanoid soccer robot. The experimental results show the performance of this controller to generate stable walking. The average speed of walking that we have achieved was 20cm/sec.

Human-Robot Collaboration and Safety Management for Logistics and Manipulation Tasks

To realize human-robot collaboration in manufacturing, industrial robots need to share an environment with humans and to work hand in hand. This introduces safety concerns but also provides the opportunity to take advantage of human-robot interactions to control the robot. The main objective of this work is to provide HRI without compromising safety issues in a realistic industrial context. In the paper, a region-based filtering and reasoning method for safety has been developed and integrated into a human-robot collaboration system. The proposed method has been successfully demonstrated keeping safety during the showcase evaluation of the European robotics challenges with a real mobile manipulator.