Katie Genter

Role-based ad hoc teamwork

An ad hoc team setting is one in which teammates must work together to obtain a common goal, but without any prior agreement regarding how to work together. In this paper we present a role-based approach for ad hoc teamwork, in which each teammate is inferred to be following a specialized role that accomplishes a specific task or exhibits a particular behavior. In such cases, the role an ad hoc agent should select depends both on its own capabilities and on the roles currently selected by the other team members. We formally define methods for evaluating the influence of the ad hoc agents role selection on the teams utility, leading to an efficient calculation of the role that yields maximal team utility. In simple teamwork settings, we demonstrate that the optimal role assignment can be easily determined. However, in complex environments, where it is not trivial to determine the optimal role assignment, we examine empirically the best suited method for role assignment. Finally, we show that the methods we describe have a predictive nature. As such, once an appropriate assignment method is determined for a domain, it can be used successfully in new tasks that the team has not encountered before and for which only limited prior experience is available.

UT Austin Villa 2012: Standard Platform League World Champions

In 2012, UT Austin Villa claimed Standard Platform League championships at both the US Open and RoboCup 2012 in Mexico City. This paper describes the key contributions that led to the team’s victories. First, UT Austin Villa’s code base was developed on a solid foundation with a flexible architecture that enables easy testing and debugging of code. Next, the vision code was updated this year to take advantage of the dual cameras and better processor of the new V4 Nao robots. To improve localization, a custom localization simulator allowed us to implement and test a full team solution to the challenge of both goals being the same color. The 2012 team made use of Northern Bites’ port of B-Human’s walk engine, combined with novel kicks from the walk. Finally, new behaviors and strategies take advantage of opportunities for the robot to take time to setup for a long kick, but kick very quickly when opponent robots are nearby. The combination of these contributions led to the team’s victories in 2012.

The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork

As the prevalence of autonomous agents grows, so does the number of interactions between these agents. Therefore, it is desirable for these agents to be capable of banding together with previously unknown teammates towards a common goal: to collaborate without pre-coordination. While past research on ad hoc teamwork has focused mainly on theoretical treatments and empirical studies in relatively simple domains, the long-term vision has been to enable robots and other autonomous agents to exhibit the sort of flexibility and adaptability on complex tasks that people do, for example when they play games of “pick-up” basketball or soccer. This paper introduces a series of pick-up robot soccer experiments that were carried out in three different leagues at the international RoboCup competition in 2013. In all cases, agents from different labs were put on teams with no pre-coordination. This paper introduces the structure of these experiments, describes the strategies used by UT Austin Villa in each challenge, and analyzes the results. The papers main contribution is the introduction of a new large-scale ad hoc teamwork testbed that can serve as a starting point for future experimental ad hoc teamwork research.

Influencing a Flock via Ad Hoc Teamwork

Flocking is an emergent behavior in which each individual agent follows a simple behavior rule that leads to a group behavior that appears cohesive and coordinated. In our work, we consider how to influence a flock using a set of ad hoc agents. Ad hoc agents are added to the flock and are able to influence the flock to adopt a desired behavior by acting as part of the flock. Specifically, we first examine how the ad hoc agents can behave to quickly orient a flock towards a target heading when given knowledge of, but no direct control over, the behavior of the flock. Then we consider how the ad hoc agents can behave to herd the flock through turns quickly but with minimal agents being separated from the flock as a result of these turns. We introduce an algorithm which the ad hoc agents can use to influence the flock. We also present detailed experimental results for our algorithm, concluding that in this setting, short-term lookahead planning improves significantly upon baseline methods and can be used to herd a flock through turns quickly while maintaining the composition of the flock.

Benchmarking robot cooperation without pre-coordination in the RoboCup Standard Platform League drop-in player competition

The Standard Platform League is one of the main competitions of the annual RoboCup world championships. In this competition, teams of five humanoid robots play soccer against each other. In 2014, the league added a new sub-competition which serves as a testbed for cooperation without pre-coordination: the Drop-in Player Competition. Instead of homogeneous robot teams that are each programmed by the same people and hence implicitly pre-coordinated, this competition features ad hoc teams, i. e. teams that consist of robots originating from different RoboCup teams and that are each running different software. In this paper, we provide an overview of this competition, including its motivation and rules. We then present and analyze the results of the 2014 competition, which gathered robots from 23 teams, involved at least 50 human participants, and consisted of fifteen 20-minute games for a total playing time of 300 minutes. We also suggest improvements for future iterations, many of which will be evaluated at RoboCup 2015.

AD HOC TEAMWORK BEHAVIORS FOR INFLUENCING A FLOCK

Ad hoc teamwork refers to the challenge of designing agents that can influence the behavior of a team, without prior coordination with its teammates. This paper considers influencing a flock of simple robotic agents to adopt a desired behavior within the context of ad hoc teamwork. Specifically, we examine how the ad hoc agents should behave in order to orient a flock towards a target heading as quickly as possible when given knowledge of, but no direct control over, the behavior of the flock. We introduce three algorithms which the ad hoc agents can use to influence the flock, and we examine the relative importance of coordinating the ad hoc agents versus planning farther ahead when given fixed computational resources. We present detailed experimental results for each of these algorithms, concluding that in this setting, inter-agent coordination and deeper lookahead planning are no more beneficial than short-term lookahead planning.

Fast and Precise Black and White Ball Detection for RoboCup Soccer

In 2016, UT Austin Villa claimed the Standard Platform League’s second place position at the RoboCup International Robot Soccer Competition in Leipzig, Germany as well as first place at both the RoboCup US Open in Brunswick, USA and the World RoboCup Conference in Beijing, China. This paper describes some of the key contributions that led to the team’s victories with a primary focus on our techniques for identifying and tracking black and white soccer balls. UT Austin Villa’s ball detection system was overhauled in order to transition from the league’s bright orange ball, used every year of the competition prior to 2016, to the truncated icosahedral pattern commonly associated with soccer balls.

Three Years of the RoboCup Standard Platform League Drop-In Player Competition: Creating and Maintaining a Large Scale Ad Hoc Teamwork Robotics Competition

The Standard Platform League is one of the main competitions at the annual RoboCup world championships. In this competition, teams of five humanoid robots play soccer against each other. In 2013, the league began a new competition which serves as a testbed for cooperation without pre-coordination: the Drop-in Player Competition. Instead of homogeneous robot teams that are each programmed by the same people and hence implicitly pre-coordinated, this competition features ad hoc teams, i.e. teams that consist of robots originating from different RoboCup teams and as such running different software. In this article, we provide an overview of this competition, including its motivation, rules, and how these rules have changed across three iterations of the competition. We then present and analyze the strategies utilized by various drop-in players as well as the results of the first three competitions before suggesting improvements for future competitive evaluations of ad hoc teamwork. To the best of our knowledge, these three competitions are the largest annual ad hoc teamwork robotic experiment to date. Across three years, the competition has seen 56 entries from 30 different organizations and consisted of 510 min of game time that resulted in approximately 85 robot hours.

UT Austin Villa: Project-Driven Research in AI and Robotics

UT Austin Villa is a robot soccer team that has competed in the annual RoboCup soccer competitions since 2003. The team has won several championships and has inspired research contributions spanning many topics in robotics and artificial intelligence. This article summarizes some of these research contributions and provides a snapshot into the current development status of the team. Educational uses of the teams code bases are also presented.

The 2012 UT Austin Villa Code Release

In 2012, UT Austin Villa claimed the Standard Platform League championships at both the US Open and the 2012 RoboCup competition held in Mexico City. This paper describes the code release associated with the team and discusses the key contributions of the release. This release will enable teams entering the Standard Platform League and researchers using the Naos to have a solid foundation from which to start their work as well as providing useful modules to existing researchers and RoboCup teams. We expect it to be of particular interest because it includes the architecture, logic modules, and debugging tools that led to the team’s success in 2012. This architecture is designed to be flexible and robust while enabling easy testing and debugging of code. The vision code was designed for easy use in creating color tables and debugging problems. A custom localization simulator that is included permits fast testing of full team scenarios. Also included is the kick engine which runs through a number of static joint poses and adapts them to the current location of the ball. This code release will provide a solid foundation for new RoboCup teams and for researchers that use the Naos.