Few disasters can inspire more compassion for victims and families than those involving structural collapse. Video clips of children's bodies pulled from earthquake stricken cities and bombing sties tend to invoke tremendous grief and sorrow because of the totally unpredictable nature of the crisis and lack of even the slightest degree of negligence (such as with those who choose to ignore storm warnings). Heartbreaking stories of people buried alive for days provide a visceral and horrific perspective of some of greatest fears ever to be imagined by human beings. Current trends toward urban sprawl and increasing human discord dictates that structural collapse disasters will continue to present themselves at an alarming rate. The proliferation of domestic terrorism, HAZMAT and biological contaminants further complicates the matter further and presents a daunting problem set for Urban Search and Rescue (USAR) organizations around the world. This paper amplifies the case for robot assisted search and rescue that was first presented during the KNOBSAR project initiated at the Colorado School of Mines in 1995. It anticipates increasing technical development in mobile robot technologies and promotes their use for a wide variety of humanitarian assistance missions. Focus is placed on development of advanced robotic systems that are employed in a complementary tool-like fashion as opposed to traditional robotic approaches that portend to replace humans in hazardous tasks. Operational challenges for USAR are presented first, followed by a brief history of mobiles robot development. The paper then presents conformal robotics as a new design paradigm with emphasis on variable geometry and volumes. A section on robot perception follows with an initial attempt to characterize sensing in a volumetric manner. Collaborative rescue is then briefly discussed with an emphasis on marsupial operations and linked mobility. The paper concludes with an emphasis on Human Robot Interface
Choi Mobi Army 220 Tren Pc
Most RF beacons-based mobile robot navigation techniques rely on approximating line-of-sight (LOS) distances between the beacons and the robot. This is mostly performed using the robot's received signal strength (RSS) measurements from the beacons. However, accurate mapping between the RSS measurements and the LOS distance is almost impossible to achieve in reverberant environments. This paper presents a partially-observed feedback controller for a wheeled mobile robot where the feedback signal is in the form of noisy RSS measurements emitted from radio frequency identification (RFID) tags. The proposed controller requires neither an accurate mapping between the LOS distance and the RSS measurements, nor the linearization of the robot model. The controller performance is demonstrated through numerical simulations and real-time experiments. 2013 Published by ISA. All rights reserved.
The TARDEC Intelligent Mobility program addresses several essential technologies necessary to support the army after next (AAN) concept. Ground forces in the AAN time frame will deploy robotic unmanned ground vehicles (UGVs) in high-risk missions to avoid exposing soldiers to both friendly and unfriendly fire. Prospective robotic systems will include RSTA/scout vehicles, combat engineering/mine clearing vehicles, indirect fire artillery and missile launch platforms. The AAN concept requires high on-road and off-road mobility, survivability, transportability/deployability and low logistics burden. TARDEC is developing a robotic vehicle systems integration laboratory (SIL) to evaluate technologies and their integration into future UGV systems. Example technologies include the following: in-hub electric drive, omni-directional wheel and steering configurations, off-road tires, adaptive tire inflation, articulated vehicles, active suspension, mine blast protection, detection avoidance and evasive maneuver. This paper will describe current developments in these areas relative to the TARDEC intelligent mobility program.
The future of robotics predicts that robots will integrate themselves more every day with human beings and their environments. To achieve this integration, robots need to acquire information about the environment and its objects. There is a big need for algorithms to provide robots with these sort of skills, from the location where objects are needed to accomplish a task up to where these objects are considered as information about the environment. This paper presents a way to provide mobile robots with the ability-skill to detect objets for semantic navigation. This paper aims to use current trends in robotics and at the same time, that can be exported to other platforms. Two methods to detect objects are proposed, contour detection and a descriptor based technique, and both of them are combined to overcome their respective limitations. Finally, the code is tested on a real robot, to prove its accuracy and efficiency. PMID:24732101
The ADAPT project is a collaboration of researchers in robotics, linguistics and artificial intelligence at three universities to create a cognitive architecture specifically designed to be embodied in a mobile robot. There are major respects in which existing cognitive architectures are inadequate for robot cognition. In particular, they lack support for true concurrency and for active perception. ADAPT addresses these deficiencies by modeling the world as a network of concurrent schemas, and modeling perception as problem solving. Schemas are represented using the RS (Robot Schemas) language, and are activated by spreading activation. RS provides a powerful language for distributed control of concurrent processes. Also, The formal semantics of RS provides the basis for the semantics of ADAPT's use of natural language. We have implemented the RS language in Soar, a mature cognitive architecture originally developed at CMU and used at a number of universities and companies. Soar's subgoaling and learning capabilities enable ADAPT to manage the complexity of its environment and to learn new schemas from experience. We describe the issues faced in developing an embodied cognitive architecture, and our implementation choices.
The U.S. Army is seeking to develop autonomous off-road mobile robots to perform tasks in the field such as supply delivery and reconnaissance in dangerous territory. A key problem to be solved with these robots is off-road mobility, to ensure that the robots can accomplish their tasks without loss or damage. We have developed a computer model of one such concept robot, the small-scale "T-1" omnidirectional vehicle (ODV), to study the effects of different control strategies on the robot's mobility in off-road settings. We built the dynamic model in ADAMS/Car and the control system in Matlab/Simulink. This paper presents the template-based method used to construct the ADAMS model of the T-1 ODV. It discusses the strengths and weaknesses of ADAMS/Car software in such an application, and describes the benefits and challenges of the approach as a whole. The paper also addresses effective linking of ADAMS/Car and Matlab for complete control system development. Finally, this paper includes a section describing the extension of the T-1 templates to other similar ODV concepts for rapid development.
To investigate the effects of controlled passive stretching and active movement training using a portable rehabilitation robot on stroke survivors with ankle and mobility impairment. Twenty-four patients at least 3 months post stroke were assigned to receive 6 week training using the portable robot in a research laboratory (robot group) or an instructed exercise program at home (control group). All patients underwent clinical and biomechanical evaluations in the laboratory at pre-evaluation, post-evaluation, and 6-week follow-up. Subjects in the robot group improved significantly more than that in the control group in reduction in spasticity measured by modified Ashworth scale, mobility by Stroke Rehabilitation Assessment of Movement (STREAM), the balance by Berg balance score, dorsiflexion passive range of motion, dorsiflexion strength, and load bearing on the affected limb during gait after 6-week training. Both groups improved in the STREAM, dorsiflexion active range of motion and dorsiflexor strength after the training, which were retained in the follow-up evaluation. Robot-assisted passive stretching and active movement training is effective in improving motor function and mobility post stroke.
Metaheuristics are general purpose heuristics which have shown a great potential for the solution of difficult optimization problems. In this work, we apply the meta heuristic, namely particle swarm optimization, PSO, for the solution of the optimization problem arising in NLMPC. This algorithm is easy to code and may be considered as alternatives for the more classical solution procedures. The PSO- NLMPC is applied to control a mobile robot for the tracking trajectory and obstacles avoidance. Experimental results show the strength of this approach.
This work presents the development and experimental evaluation of a method based on fuzzy logic to locate mobile robots in an Intelligent Space using wireless sensor networks (WSNs). The problem consists of locating a mobile node using only inter-node range measurements, which are estimated by radio frequency signal strength attenuation. The sensor model of these measurements is very noisy and unreliable. The proposed method makes use of fuzzy logic for modeling and dealing with such uncertain information. Besides, the proposed approach is compared with a probabilistic technique showing that the fuzzy approach is able to handle highly uncertain situations that are difficult to manage by well-known localization methods.
We present a survey of multi-robot assembly applications and methods and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic systems. Such robotic systems include industrial robot arms, dexterous robotic hands, and autonomous mobile platforms, such as automated guided vehicles. In this survey, we identify the types of assemblies that are enabled by utilizing multiple robots, the algorithms that synchronize the motions of the robots to complete the assembly operations, and the metrics used to assess the quality and performance of the assemblies. 2ff7e9595c
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