The DARPA Robotics Challenge (DRC) program conducted a series of prize‐based competition events to develop and demonstrate technology for disaster response. This article provides the official and definitive account of DRC Finals as the culmination of the DRC program. The article details the eight tasks (Drive, Egress, Door, Valve, Wall, Surprise [Plug and Switch], Rubble [Obstacle or Debris], and Stairs) constituting the Challenge, and describes how the competition encouraged supervised autonomous operation by intentionally degrading the communications channel between the remote human operators. The article presents the results of the DRC Finals and places those results in perspective by identifying both strengths and weaknesses of robot performance exhibited at the competition.

This paper presents the software framework established to facilitate cloud-hosted robot simulation. The framework addresses the challenges associated with conducting a task-oriented and real-time robot competition, the Defense Advanced Research Projects Agency (DARPA) Virtual Robotics Challenge (VRC), designed to mimic reality. The core of the framework is the Gazebo simulator, a platform to simulate robots, objects, and environments, as well as the enhancements made for the VRC to maintain a high fidelity simulation using a high degree of freedom and multisensor robot. The other major component used is the CloudSim tool, designed to enhance the automation of robotics simulation using existing cloud technologies. The results from the VRC and a discussion are also detailed in this work. Note to Practitioners - Advances in robot simulation, cloud hosted infrastructure, and web technology have made it possible to accurately and efficiently simulate complex robots and environments on remote servers while providing realistic data streams for human-in-the-loop robot control. This paper presents the software and hardware frameworks established to facilitate cloud-hosted robot simulation, and addresses the challenges associated with conducting a task-oriented robot competition designed to mimic reality. The competition that spurred this innovation was the VRC, a precursor to the DARPA Robotics Challenge, in which teams from around the world utilized custom human-robot interfaces and control code to solve disaster response-related tasks in simulation. Winners of the VRC received both funding and access to Atlas, a humanoid robot developed by Boston Dynamics. The Gazebo simulator, an open source and high fidelity robot simulator, was improved upon to met the needs of the VRC competition. Additionally, CloudSim was created to act as an interface between users and the cloud-hosted simulations. As a result of this work, we have achieved automated deployment of cloud resources for robotic simulations, near real-time simulation performance, and simulation accuracy that closely mimics real hardware. These tools have been released under open source licenses and are freely available, and can be used to help reduce robot and algorithm design and development time, and increase robot software robustness.

About half a billion years ago, life on earth experienced a short period of very rapid diversification called the "Cambrian Explosion." Many theories have been proposed for the cause of the Cambrian Explosion, one of the most provocative being the evolution of vision, allowing animals to dramatically increase their ability to hunt and find mates. Today, technological developments on several fronts are fomenting a similar explosion in the diversification and applicability of robotics. Many of the base hardware technologies on which robots depend-particularly computing, data storage, and communications-have been improving at exponential growth rates. Two newly blossoming technologies-"Cloud Robotics" and "Deep Learning"-could leverage these base technologies in a virtuous cycle of explosive growth. I examine some key technologies contributing to the present excitement in the robotics field. As with other technological developments, there has been a significant uptick in concerns about the societal implication of robotics and artificial intelligence. Thus, I offer some thoughts about how robotics may affect the economy and some ways to address potential difficulties.

The Defense Advanced Research Projects Agency (DARPA) has funded innovative scientific research and technology developments in the field of brain-computer interfaces (BCI) since the 1970s. This review highlights some of DARPA's major advances in the field of BCI, particularly those made in recent years. Two broad categories of DARPA programs are presented with respect to the ultimate goals of supporting the nation's warfighters: (1) BCI efforts aimed at restoring neural and/or behavioral function, and (2) BCI efforts aimed at improving human training and performance. The programs discussed are synergistic and complementary to one another, and, moreover, promote interdisciplinary collaborations among researchers, engineers, and clinicians. Finally, this review includes a summary of some of the remaining challenges for the field of BCI, as well as the goals of new DARPA efforts in this domain. (C) 2014 The Authors. Published by Elsevier B.V.

This paper summarizes an ongoing research program to advance the state of the art in robotics: the U.S. Defense Advanced Research Projects Agency Autonomous Robotic Manipulation (ARM) program. The program began in 2010 with three tracks, which was later extended to four. The software track is developing intelligent control of manipulators to perform autonomous tasks, using local perception sensors. The hand track has developed rugged, dexterous, multi-fingered hands with significantly reduced costs. The arm track is working to reduce the cost of robot arms. And the outreach track is showcasing robot technology to the general public. Technology developed under the program is iteratively evaluated through a series of hands-off tests. To date, the ARM developers have performed beyond expectations, yielding outstanding hardware designs and robust manipulation software. The results of this program are expected to strengthen the general robotics community and transition technology to U.S. military efforts.

The 2011 disaster at the Fukushima Daiichi Nuclear Power Plant highlighted the promise and shortcomings of robots. Had robots been able to quickly enter the plant and vent accumulated hydrogen, a meltdown could have been averted, but training requirements and technology limitations delayed their deployment. The US Defense Advanced Research Projects Agency launched the DARPA Robotics Challenge to catalyze development of semi-autonomous robots capable of operating in dangerous, degraded environments so society is prepared to respond to future disasters. The challenge brings together robotics systems and software experts from around the world in a series of competitions to overcome technological obstacles related to robotic mobility, manipulation, perception, human-robot interface, and actuation. Over a period of less than three years, DARPA expects the field of robotics to undergo a historic transformation that could drive innovation in robots for defense, health care, agriculture, and industry. DARPA outlines its objectives for the challenge, addresses the ethics and present realities of robotics, and charts the development path to capable, cost-effective systems.

The U.S. Defense Advanced Research Projects Agency's (DARPA) Neovision2 program aims to develop artificial vision systems based on the design principles employed by mammalian vision systems. Three such algorithms are briefly described in this paper. These neuromorphic-vision systems' performance in detecting objects in video was measured using a set of annotated clips. This paper describes the results of these evaluations including the data domains, metrics, methodologies, performance over a range of operating points and a comparison with computer vision based baseline algorithms.

This paper summarizes an ongoing research program to advance the state of the art in robotics: the U.S. Defense Advanced Research Projects Agency Autonomous Robotic Manipulation (ARM) program. The program began in 2010 with three tracks, which was later extended to four. The software track is developing intelligent control of manipulators to perform autonomous tasks, using local perception sensors. The hand track has developed rugged, dexterous, multi-fingered hands with significantly reduced costs. The arm track is working to reduce the cost of robot arms. And the outreach track is showcasing robot technology to the general public. Technology developed under the program is iteratively evaluated through a series of hands-off tests. To date, the ARM developers have performed beyond expectations, yielding outstanding hardware designs and robust manipulation software. The results of this program are expected to strengthen the general robotics community and transition technology to U.S. military efforts. D. Hackett (B) Griffin Technologies, Fort Washington, PA, USA e-mail: dhackett@griffin-technologies.com J. Pippine Golden Knight Technologies, Fairfax, VA, USA e-mail: Jim@goldenknighttechnologies.com A. Watson · C. Sullivan Mechanismo, Reston, VA, USA e-mail: adam@mechanismollc.com C. Sullivan e-mail: chad@mechanismollc.com G. Pratt Defense Advanced Research Projects Agency (DARPA), Arlington, VA, USA e-mail: gpratt@darpa.mil

SUMMARY Series elastic actuators have beneficial properties for some robot applications. Several recent implementations contain alternative placements of the compliant element to improve instrumentation design. We use a class 1 versus class 2 lever model and energy-port methods to demonstrate in this paper that these alternative placements should still be classified as series elastic actuators. We also note that the compliance of proximal series elastic actuators is reflected by an augmented gear ratio dependent on the nominal gear ratio, which is significant for small gear ratios and approaches unity for large gear ratios. This reflected compliance is shown to differ depending on the sign of the gear ratio. We demonstrate that although the reflected compliance is only marginally influenced by the magnitude of the gear ratio, there are several notable differences, particularly for small gear ratios.

Circa 2010, manipulation systems required burdensome human operation and high-precision arms and hands, yet could not match the manipulation skills of a two-year old child.To address this situation, the U.S.

views, opinions, and/or findings contained in this article/presentation are those of the author/ presenter and should not be interpreted as represent-ing the official views or policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the Department of Defense.

ny news broadcast reveals that Mother Nature and human nature are not always on our side. Shifting demographics make society increasingly susceptible to both natural and man-made disasters. Densely populated coastal cities prone to flooding and bad weather invite heavy tolls from natural disasters. Manmade disasters come in many forms, such as chemical spills, weapons of mass destruction, release of radiation, and so on. Humanity must improve its defenses against such threats, i.e., we must prepare for the unexpected. During the Fukushima disaster, many Japanese citizens, aware of the development of humanoid robotic platforms, asked, “Can’t robots help us?” It turns out that they could not, at least not then. The Defense Advanced Research Projects Agency (DARPA) Robotics Challenge (DRC) aims to work up to robots that can help in the near future. The DRC is a program in human-scaled robotics for disaster response. DARPA’s goal is to create robots that could interface with human environments, use human tools, and be commanded by humans without specialized training. We want robots that can adapt to assist in any disaster.

This invention is an electronically commutated brushless motor contro ller that incorporates Hall-array sensing in a small, 42-gram packag e that provides 4096 absolute counts per motor revolution position s ensing. The unit is the size of a miniature hockey puck, and is a 44 -pin male connector that provides many I/O channels, including CANbus , RS-232 communications, general-purpose analog and digital I/O (GPI O), analog and digital Hall inputs, DC power input (18-90 VDC, 0-l0 A), three-phase motor outputs, and a strain gauge amplifier.