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BlueBotics: Navigation for the Clever Robot By Nicola Tomatis
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lueBotics’ story started because of the Swiss National Exhibition in 2002. At that time, the Autonomous Systems Laboratory (directed by Prof. Roland Siegwart) was commissioned to develop tour-guide robots, which had to lead hundreds of visitors per day through a part of the exhibition specially dedicated to robotics. A team of 25 scientists and artists was set in place to work on mechatronics, navigation, and interaction aspects, and after several months of intensive work, the tour-guide robot RoboX was born. During the six months of the exhibition, 11 RoboXes dispensed information to more than 680,000 visitors, worked uncomplainingly for 13,000 h, and covered more than 3,000 km. The visitors were enthusiastic about the robots, and the level of professional experience gained through this event was important for the spin-off to focus on this first niche market. At the beginning, there were just four of us, each one with a specific focus in computer science, mechanics, or electronics. Our goal was to market innovative and promising mobile robotics technologies. We were optimistic in thinking, maybe naively at the time, that the industry was just waiting for our mobile robotics solutions to emerge.
We are interested in publishing articles for this column focusing on successful past and ongoing industrial research projects and implementations worldwide. The objective is to inform IEEE Robotics & Automation Magazine readers of successes, challenges, and lessons learned from all aspects of the robotics and automation industry, including short- and long-term visions. The articles can be four to five pages in length and will undergo a review process consistent with the magazine’s policy. Send an e-mail to Raj Madhavan, industry editor, at
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tour guide, and Shrimp, a research platform for space exploration, did not allow us to grow as fast as we’d liked to. The mobile robotics market is indeed very restricted, expectations are high, and the cost of the systems is often prohibitive. It was however a strong decision for us to be selffinanced from the beginning. We used our know-how to develop robotics and mechatronics systems for various customers and invested our benefits in the development of autonomous navigation technology (ANT) our
From Research to Industry The real world proved tougher though. Our first two products, RoboX, the
Digital Object Identifier 10.1109/MRA.2011.941629
Figure 1 Nesbot mobile coffee.
Date of publication: 14 June 2011
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Editor’s Note
autonomous navigation product. This proved a slow way to go but gave us the chance to work on many projects, with visionary and stimulating industrial partners. In 2007, for example, Nesbot caused a sensation at the International Conference on Robotics and Automation in Rome when the robot served up to 150 coffees a day to visitors (see Figure 1). This fully autonomous and completely embedded mobile coffee machine with user interfaces for professional services—developed together with Nestle Nespresso SA—shows how an independent serving platform can radically change the art of beverage and food ordering. In a completely different type of application, on behalf of the European Space Agency (ESA), our engineers participated in various development phases of the ExoMars mission by developing and producing all the rovers for the latest B2 phase. In another innovative partnership, we collaborated with Esatroll SA, an Italian firm specializing in automated guided vehicles (AGVs), to create Gilberto, the robot guide and information desk, which is now in exploitation in several museums and theme parks (Figure 2).
• Further collaborating with Autonomous Systems LaboEsatroll, we made use of their ratory [1], [2]. l Map—The map of the cost-efficient forklift for logistics environment is a graphand launched Paquito (Figure 3), like structure with nodes an industrial forklift running representing positions the with a payload of 1,200 kg, robot has to reach in order moving autonomously and to perform a certain task. safely through factory buildFurthermore it contains ings. Since 2009, the ANTthe information about driven Paquitos have been all the features in the enoffering their services to vironment, which are different Italian companies either segments (walls, working 24 h a day, 7 days furniture, or other struca week on production tures) or points (table’s chains. legs, other furniture, A new wind was Figure 2 Gilberto guide. or, when needed, reflecblowing in 2010 with tors). This permits to the collaboration with calculate which feature is visible from KOKEISL Industrial Systems AG, an the current position of the robot and international vendor and system proto use it for localization. vider of automated systems for the bulk solids industry and AGVs (Figure 4). l Localization—The ANT localization implements an extended KalOur joint work resulted in the KOKEISL man filter [3]. The filter uses the picking robot (KPR), a modularly built wheel encoder to calculate the odovehicle powered by ANT. The robot is a metrical position and integrates the multitalented one, collecting bulk mateextracted features presented above rials from different batches from a few in a weighted manner based on kilograms to two tons. Working in their uncertainty. The use of these harmony with the law of gravity, the features makes the position estiKPR gathers materials vertically. Using mation highly robust in dynamic automatic shovels, it can dose and asenvironments. semble formulas and small quantities accurately to the nearest gram. The l Global planning—The global planning is based on the aforemenKPR can autonomously withdraw matetioned graph structure, where the rials from almost any container in the nodes are locations of interest and plant and looks after the transport edges denote traversability between between the warehouse, the dispenslocations. The planner employs a ing terminals, and the mixing stations depth-first search and generates a with a positioning precision of 610 mm, length-optimal path. thanks to ANT. ANT—Our Core Technology The recurrent theme in all these developments is ANT, which has over time become our main focus and most successful product. ANT is an environment-based navigation system that can be installed on literally any type of mobile system requiring localization and navigation skills. ANT uses several components to implement the navigation tasks, such as map, localization, global planning, and motion control. These components are extensions of the technologies formerly developed at the
Figure 3 Esatroll’s Paquito.
• Motion control—Two different approaches are used depending on the application. For service robotics applications, we use a combination of three algo• rithms. The NF1 Many experts predict navigation function [4] initialthat the 21st century izes the motion will be a century of path in a local grid around robotics. robot. Then • the the elastic band approach [5] guarantees a smooth dynamic adaptation of the path, taking into account the obstacles around the robot. Finally, the dynamic window method [6] ensures that the robot uses the best speed guaranteeing collision-free movements. In the industrial logistics, we use a path follower implementing cubic splines curves combined with a reduced dynamic window method. l
Figure 4 Kokeisl’s KPR.
l l
All this builds up two main benefits: no need to change the environment vehicles can autonomously handle obstacles and move within a defined area.
In the logistics industry, this makes the vehicles adaptable to new automation processes such as free pallet positioning, load transfer to trucks, or deep stacking. Today, we often hear the question: Many companies do environmentbased navigation, and in what way is your technology different? It is true: environment-based navigation is nothing new to the scientific world; in fact, the theory behind our product was developed in the 1990s. Our difference lies in the ten years of field experience that allowed us to face and solve hundreds of small real-life problems and, most of all, learn how to listen and answer to the needs of our industrial customers. It is no secret. Many experts predict that the 21st century will be a century of robotics. Only time will tell if they will be proven right. Whatever happens, with our decade of experience in the field, we feel ready to face the challenges that will accompany a rapid growth of the service robotics industry. References [1] K. O. Arras, N. Tomatis, B. Jensen, and R. Siegwart, “Multisensor on-the-fly localization: Precision and reliability for applications,” Robot. Autonom. Syst., vol. 34, nos. 2–3, pp. 131– 143, 2001. [2] N. Tomatis, G. Terrien, R. Piguet, D. Buriner, S. Bouabdallah, K. O. Arras, and R. Siegwart, “Designing a secure and robust mobile interacting robot for the long term,” in Proc. IEEE Int. Conf. Robotics and Automation, Taipei, Taiwan, 2003. [3] J. L. Crowley, “World modeling and position estimation for a mobile robot using ultrasonic ranging,” in Proc. IEEE Int. Conf. Robotics and Automation, Scottsdale, AZ, 1989. [4] J.-C. Latombe, Robot Motion Planning, Dordrecht Netherlands, Kluwer Academic, 1991. [5] S. Quinlan and O. Khatib, “Elastic bands: connecting path planning and control,” in Proc. IEEE Int. Conf. Robotics and Automation, 1993. [6] D. Fox and W. Burgard, et al., “The dynamic window approach to collision avoidance,” IEEE Robot. Automat. Mag., pp. 23–33, 1997.
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