Tim Niemueller

Herb 2.0: Lessons Learned From Developing a Mobile Manipulator for the Home

We present the hardware design, software architecture, and core algorithms of Herb 2.0, a bimanual mobile manipulator developed at the Personal Robotics Lab at Carnegie Mellon University, Pittsburgh, PA. We have developed Herb 2.0 to perform useful tasks for and with people in human environments. We exploit two key paradigms in human environments: that they have structure that a robot can learn, adapt and exploit, and that they demand general-purpose capability in robotic systems. In this paper, we reveal some of the structure present in everyday environments that we have been able to harness for manipulation and interaction, comment on the particular challenges on working in human spaces, and describe some of the lessons we learned from extensively testing our integrated platform in kitchen and office environments.

Design principles of the component-based robot software framework Fawkes

The idea of component-based software engineering was proposed more that 40 years ago, yet only few robotics software frameworks follow these ideas. The main problem with robotics software usually is that it runs on a particular platform and transferring source code to another platform is crucial. In this paper, we present our software framework Fawkes which follows the component-based software design paradigm by featuring a clear component concept with well-defined communication interfaces. We deployed Fawkes on several different robot platforms ranging from service robots to biped soccer robots. Following the component concept with clearly defined communication interfaces shows great benefit when porting robot software from one robot to the other. Fawkes comes with a number of useful plugins for tasks like timing, logging, data visualization, software configuration, and even high-level decision making. These make it particularly easy to create and to debug productive code, shortening the typical development cycle for robot software.

RoboCup Logistics League Sponsored by Festo: A Competitive Factory Automation Testbed

A new trend in automation is to deploy so-called cyber-physical systems (CPS) which combine computation with physical processes. The novel RoboCup Logistics League Sponsored by Festo (LLSF) aims at a such CPS logistic scenarios in an automation setting. A team of robots has to produce products from a number of semi-finished products which they have to machine during the game. Different production plans are possible and the robots need to recycle scrap byproducts. This way, the LLSF is a very interesting league offering a number of challenging research questions for planning, coordination, or communication in an application-driven scenario. In this paper, we outline the objectives of the LLSF and present steps for developing the league further towards a benchmark for logistics scenarios for CPS. As a major milestone we present the new automated referee system which helps in governing the game play as well as keeping track of the scored points in a very complex factory scenario.

A generic robot database and its application in fault analysis and performance evaluation

During operation of robots large amounts of data are produced and processed for instance in perception, actuation, or decision making. Nowadays this data is typically volatile and disposed right after use. But this data can be valuable and useful later. Therefore we propose a database system that taps into common robot middleware to record any and all data produced at run-time. We present two examples using this data in fault analysis and performance evaluation and describe real-world experiments run on the domestic service robot HERB.

Simulation for the RoboCup Logistics League with Real-World Environment Agency and Multi-level Abstraction

RoboCup is particularly well-known for its soccer leagues, but there are an increasing number of application leagues. The newest one is the Logistics League where groups of robots take on the task of in-factory production logistics. It has two unique aspects: a game environment which itself acts as an agent and a focus on planning and scheduling in robotics. We propose a simulation based on Gazebo that takes these into account. It uses the exact same referee box to simulate the environment reactions similar to the real game and it supports multiple levels of abstraction that allow to focus on the planning with a high level of abstraction, or to run the full system on simulated sensor data on a lower level for rapid integration testing. We envision that this simulation could be a basis for a simulation sub-league for the LLSF to attract a wider range of participants and ease entering the robot competition.

Towards Benchmarking Cyber-Physical Systems in Factory Automation Scenarios

A new trend in automation is to deploy so-called cyber-physical systems (CPS) which combine computation with physical processes. In future factory automation scenarios, mobile robots will play an important role to help customizing the production process, for instance, by transporting semi-products and raw materials to the machines. Therefore it will be important to compare the performance of mobile robots in such future logistics tasks. In this paper we sketch how the novel RoboCup Logistics League with its automated referee and overhead tracking system can be developed into a standard benchmark for logistics application in factory automation scenarios.

Evaluation of the RoboCup Logistics League and Derived Criteria for Future Competitions

In the RoboCup Logistics League RCLL, games are governed by a semi-autonomous referee box. It also records tremendous amounts of data about state changes of the game or communication with the robots. In this paper, we analyze the data of the 2014 competition by means of Key Performance Indicators KPI. KPIs are used in industrial environments to evaluate the performance of production systems. Applying adapted KPIs to the RCLL provides interesting insights about the strategies of the robot teams. When aiming for more realistic industrial properties with a 24/7 production, where teams perform shifts without intermediate environment reset, KPIs could be a means to score the game. This could be tried first in a simulation sub-league.

Decisive Factors for the Success of the Carologistics RoboCup Team in the RoboCup Logistics League 2014

The RoboCup Logistics League is one of the youngest application- and industry-oriented leagues. Even so, the complexity and level of difficulty has increased over the years. We describe decisive technical and organizational aspects of our hardware and software systems and (human) team structure that made winning the RoboCup and German Open competitions possible in 2014.

On the Synthesis of Guaranteed-Quality Plans for Robot Fleets in Logistics Scenarios via Optimization Modulo Theories

In manufacturing, the increasing involvement of autonomous robots in production processes poses new challenges on the production management. In this paper we report on the usage of Optimization Modulo Theories (OMT) to solve certain multi-robot scheduling problems in this area. Whereas currently existing methods are heuristic, our approach guarantees optimality for the computed solution. We do not only present our final method but also its chronological development, and draw some general observations for the development of OMT-based approaches.

Knowledge-Based Instrumentation and Control for Competitive Industry-Inspired Robotic Domains

Autonomy is an increasing trend in manufacturing industries. Several industry-inspired robotic competitions have been established in recent years to provide testbeds of comprehensible size. In this paper, we describe a knowledge-based instrumentation and control framework used in several of these competitions. It is implemented using a rule-based production system and creates the task goals for autonomous mobile robots. It controls the environment’s agency using sensor data from processing stations and instructs proper reactions. The monitoring and collection of various data allows for an effective instrumentation of the competitions for evaluation purposes. The goal is to achieve automated runs with no or as little human intervention as possible which would allow for more and longer lasting runs. It provides a general framework adaptable to suit many scenarios and is an interesting test case for knowledge-based systems in an industry-inspired setting.