In this video we briefly illustrate the progress and contributions made with our mobile, indoor, service robots CoBots (Collaborative Robots), since their creation in 2009. Many researchers, present authors included, aim for autonomous mobile robots that robustly perform service tasks for humans in our indoor environments. The efforts towards this goal have been numerous and successful, and we build upon them. However, there are clearly many research challenges remaining until we can experience intelligent mobile robots that are fully functional and capable in our human environments. Our research and continuous indoor deployment of the CoBot robots in multi-floor office-style buildings provides multiple contributions, including: robust real-time autonomous localization [1] , based on WIFI data [2] , and on depth camera information [3] ; symbiotic autonomy in which the deployed robots can overcome their perceptual, cognitive, and actuation limitations by proactively asking for help from humans [4], [5] , and, in ongoing experiments, from the web [6], [7] , and from other robots [8], [9] ; human-centered planning in which models of humans are explicitly used in robot task and path planning [10] ; semiautonomous telepresence enabling the combination of rich remote visual and motion control with autonomous robot localization and navigation [11] ; web-based user task selection and information interfaces [12] ; and creative multi-robot task scheduling and execution [12] . Furthermore, we have developed a 3D simulation of the multi-floor, multi-person environment which will allow extensive learning experiments to provide approximate initial models and parameters to be refined with the real robots' experiences. Finally, our robot platform is extremely effective, in particular with its stable low-clearance, omnidirectional base. The CoBot robots were designed and built by Michael Licitra, (mlicitra@cmu.edu), and the base is a scaled-up version of the CMDragons small-size soccer robots [13] , also designed and built by Licitra. Remarkably, the robots have operated over 200km for more than three years without any hardware failures, and with minimal maintenance. Our robots purposefully include a modest variety of sensing and computing devices, including the Microsoft Kinect depth-camera, vision cameras for telepresence and interaction, a small Hokuyo LIDAR for obstacle avoidance and localization comparison studies (no longer present in the most recent CoBot-4), a touch-screen and speech-enabled tablet, microphones and speakers, as well as wireless signal access and processing. The CoBot robots can perform multiple classes of tasks: • A single destination task, in which the user asks the robot to go to a specific location-the Go-To-Room task-and, in addition, to deliver a specified spoken message-the Deliver-Message task; • An item transport task, in which the user requests the robot to retrieve an item at a specified location, and to deliver it to a destination location: this Transport task also acts as the task to accompany a person between locations when the item to transport is a person. • A task to escort a person to a specified location, the Escort task, in which the robot waits for a person in front of the elevator on the floor of the destination location, and guides the person to the location. • A semi-autonomous telepresence task, the Telepresence task, in which users may request to be remotely present on the mobile robot with autonomous navigation and obstacle avoidance. Users select destination points on the map or on the robot image view to move to remotely through the telepresence web interface. Furthermore, they can control the robot through a rich motion and perception-controlled web-based interface [11] . The above tasks are equivalent from a navigational point of view, as they are achieved by the same navigation planner generating plans to reach destinations in the building. A task planner generates different interaction plans for each task and its symbiotic autonomy needs. We are currently focusing on several research directions: multi-modal speech interaction, interactions among our multiple robots, learning from human demonstration, human observation, and human correction. We continue to investigate depth-based camera 3D image processing for object and person detection and person following. We further investigate robust execution monitoring, and active learning for learning of the environment and effective factored humanrobot interaction plans.
The CoBot service robots REF operate in an office building performing a variety of tasks.
CoBots: Collaborative robots servicing multi-floor buildings
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
Computer Science