Abstract-Simulation has been the dominant research methodology in wireless and sensor networking. When mobility is added, real-world experimentation is especially rare. However, it is becoming clear that simulation models do not sufficiently capture radio and sensor irregularity in a complex, real-world environment, especially indoors. Unfortunately, the high labor and equipment costs of truly mobile experimental infrastructure present high barriers to such experimentation.We describe our experience in creating a testbed to lower those barriers. We have extended the Emulab network testbed software to provide the first remotely-accessible mobile wireless and sensor testbed. Robots carry motes and single board computers through a fixed indoor field of sensor-equipped motes, all running the user's selected software. In real-time, interactively or driven by a script, remote users can position the robots, control all the computers and network interfaces, run arbitrary programs, and log data. Our mobile testbed provides simple path planning, a vision-based tracking system accurate to 1 cm, live maps, and webcams. Precise positioning and automation allow quick and painless evaluation of location and mobility effects on wireless protocols, location algorithms, and sensor-driven applications. The system is robust enough that it is deployed for public use.We present the design and implementation of our mobile testbed, evaluate key aspects of its performance, and describe a few experiments demonstrating its generality and power.

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Teleoperated robots generally receive high level commands from a remote system, while accomplishing motion control through conventional means. We present a teleoperated system that removes the entire motion control structure from the robot, in order to preserve the availability of crucial onboard resources. The operation of state feedback control is performed by a system remote from the robot. We have designed a computerized motion planning and control system for Mobile Emulab, and in this article, discuss the implementation of trajectory tracking control. A component of the Emulab network testbed, Mobile Emulab is used for wireless network experiments requiring mobility; and is publicly available to remote researchers via the Internet. Medium scale wheeled mobile robot couriers are used to move wireless antennas within a semi-controlled environment. Experimenters use a web-based GUI to specify desired paths and configurations for multiple robots. State feedback is provided by an overhead camera based visual localization system. Kinematic control is used to generate velocity commands, which are sent to robots over a computer network. Data availability is restricted to a low sampling frequency. There is significant noise, loss, and phase lag present in the robot localization data, which our research overcomes to provide an autonomous trajectory tracking mobile robot control system.

Contemporary problem formulation methods used in the dynamic simulation of rigid bodies suffer from problems in accuracy, performance, and robustness. Significant allowances for parameter tuning, coupled with careful implementation of a broad-phase collision detection scheme are required to make dynamic simulation useful for practical applications. A constraint formulation method is presented herein that is more robust, and not dependent on broad-phase collision detection or system tuning for its behavior. Several uncomplicated benchmark examples are presented to give an analysis and make a comparison of the new polyhedral exact geometry (PEG) method with the well-known Stewart–Trinkle method. The behavior and performance for the two methods are discussed. This includes specific cases where contemporary methods fail to match theorized and observed system states in simulation, and how they are ameliorated by the new method presented here. The goal of this work is to complete the groundwork for further research into high performance simulation.