Intuitive Teleoperation of an Intelligent Robotic System Using Low-Cost 6-DOF Motion Capture

There is currently a wide variety of six degree-of-freedom (6-DOF) motion capture technologies available. However, these systems tend to be very expensive and thus cost prohibitive. A software system was developed to provide 6-DOF motion capture using the Nintendo Wii remote’s (wiimote) sensors, an infrared beacon, and a novel hierarchical linear-quaternion Kalman filter. The software is made freely available, and the hardware costs less than one hundred dollars. Using this motion capture software, a robotic control system was developed to teleoperate a 6-DOF robotic manipulator via the operator’s natural hand movements. The teleoperation system requires calibration of the wiimote’s infrared cameras to obtain an estimate of the wiimote’s 6-DOF pose. However, since the raw images from the wiimote’s infrared camera are not available, a novel camera-calibration method was developed to obtain the camera’s intrinsic parameters, which are used to obtain a low-accuracy estimate of the 6-DOF pose. By fusing the low-accuracy estimate of 6-DOF pose with accelerometer and gyroscope measurements, an accurate estimation of 6-DOF pose is obtained for teleoperation. Preliminary testing suggests that the motion capture system has an accuracy of less than a millimetre in position and less than one degree in attitude. Furthermore, whole-system tests demonstrate that the teleoperation system is capable of controlling the end effector of a robotic manipulator to match the pose of the wiimote. Since this system can provide 6-DOF motion capture at a fraction of the cost of traditional methods, it has wide applicability in the field of robotics and as a 6-DOF human input device to control 3D virtual computer environments

NeBula: Team CoSTAR's robotic autonomy solution that won phase II of DARPA Subterranean Challenge

This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge. Specifically, it presents the techniques utilized within the Tunnel (2019) and Urban (2020) competitions, where CoSTAR achieved second and first place, respectively. We also discuss CoSTAR¿s demonstrations in Martian-analog surface and subsurface (lava tubes) exploration. The paper introduces our autonomy solution, referred to as NeBula (Networked Belief-aware Perceptual Autonomy). NeBula is an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states). We discuss various components of the NeBula framework, including (i) geometric and semantic environment mapping, (ii) a multi-modal positioning system, (iii) traversability analysis and local planning, (iv) global motion planning and exploration behavior, (v) risk-aware mission planning, (vi) networking and decentralized reasoning, and (vii) learning-enabled adaptation. We discuss the performance of NeBula on several robot types (e.g., wheeled, legged, flying), in various environments. We discuss the specific results and lessons learned from fielding this solution in the challenging courses of the DARPA Subterranean Challenge competition.The work is partially supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004), and Defense Advanced Research Projects Agency (DARPA)

Intelligence by Design: Principles of Modularity and Coordination for Engineerin

All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dissertation describes an approach, Behavior-Oriented Design (BOD) for engineering complex agents. A complex agent is one that must arbitrate between potentially conflicting goals or behaviors. Behavior-oriented design builds on work in behavior-based and hybrid architectures for agents, and the object oriented approach to software engineering. The primary contributions of this dissertation are: 1.The BOD architecture: a modular architecture with each module providing specialized representations to facilitate learning. This includes one pre-specified module and representation for action selection or behavior arbitration. The specialized representation underlying BOD action selection is Parallel-rooted, Ordered, Slip-stack Hierarchical (POSH) reactive plans. 2.The BOD development process: an iterative process that alternately scales the agent's capabilities then optimizes the agent for simplicity, exploiting tradeoffs between the component representations. This ongoing process for controlling complexity not only provides bias for the behaving agent, but also facilitates its maintenance and extendibility. The secondary contributions of this dissertation include two implementations of POSH action selection, a procedure for identifying useful idioms in agent architectures and using them to distribute knowledge across agent paradigms, several examples of applying BOD idioms to established architectures, an analysis and comparison of the attributes and design trends of a large number of agent architectures, a comparison of biological (particularly mammalian) intelligence to artificial agent architectures, a novel model of primate transitive inference, and many other examples of BOD agents and BOD development

Dynamically reconfigurable Artificial Sensate Skin

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (p. 207-211).The idea of an Artificial Sensate Skin device that mimics the characteristics and functions of its analogous living tissue whether human or animal is not new. Yet, most of the current related work has been focused in the development of either materials, flexible electronics or ultra-dense sensing matrices and Wide Area Sensor Networks. The current work describes the design and implementation of a new type of Artificial Sensate Skin. This Artificial Sensate Skin is implemented as a low-power, highly scalable and mechanically flexible Wired Sensor Network. This Skin is composed of one or many Skin Patches which in turn are composed of one or many Skin Nodes. Each node is able to measure Strain, Pressure, Ambient Light, Pressure, Sound and Mechanoreception. Each Skin Patch can either work as a stand-alone device or as a data extraction device if this is attached to a Personal Computer through a different type of device referred to as Brains. Each Skin Node and therefore each Skin Patch :is Dynamically Adaptable meaning that they can adapt to external stimuli by either modifying their behavior or by completely changing their code.(cont.) Construction of a sensate skin in such a modular fashion promises intrinsic scalability, where peer-to-peer connections between neighbors can reduce local data, which can then be sent to the brain by the high-speed common backbone. The current project also involves the design and implementation of the software components needed; these include a PC Graphical User Interface, application software and the firmware required by the embedded microcontrollers. Results show that needed resources like bandwidth are greatly minimized because of the addition of embedded processing power. Results also indicate that the platform can be used as a scalable smart material to cover interactive surfaces, or simply to extract a rich set of dense multi-modal sensor data.by Gerardo Barroeta Pérez.S.M

Towards Fault Diagnosis in Reconfigurable Robot

東京電機大学201

Climbing and Walking Robots

Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

Techniques to Leverage RF Signals for Context Sensing

RF signals and devices have been used for wireless communication to improve the mobility and ubiquity of mobile devices. In this dissertation, we show that these RF signals can also be used for context sensing applications. Specifically, we present cyber-physical systems and algorithms to sense human vital signals, object vibrations and movements, and object’s location to deliver new sensing capabilities for a variety of new applications including health-care monitoring, privacy protection, and indoor localization. We deliver three fundamental contributions. First, we develop an RF-based system to “sense” human breathing volume continuously in fine-grained from afar. Second, we develop a technique to “sense” the wireless signals emitted from drones/fly-cams to detect them and alert users for privacy protection. Last, we present our preliminary study on building a system to enable the mobile device to “sense” their global locations at the indoor environment. To deliver these contributions, we exploit the properties of physical characteristics of RF signals, analyze and understand targeted subjects behaviors (i.e., human, drones), work across different limitations and hardware-software barriers, and introduce novel systems and new algorithms to overcome the challenges. We implement and evaluate the system on real users/patients, test the systems across different environments, and demonstrate how they can enable many other real-world applications