We present NIMS3D, a novel 3-D cabled robot for actuated sensing applications. We provide a brief overview of the main hardware components. Next, we describe installation procedures, including novel calibration methods, that enable rapid in-field deployability for nonexpert end users, and provide simulations and experimental results to highlight their effectiveness. Kinematic and dynamic analysis of the system are provided, followed by a description of control methods. We provide experimental results that illustrate tracking of linear and nonlinear paths by NIMS3D. Thereafter, we briefly present an example of an actuated sensing task performed by the system. Finally, we describe methods of improving energy efficiency by leveraging nonlinear trajectories and energy-optimal tension distributions. Experimental and simulated results show that energy efficiency can be improved significantly by using optimized parabolic trajectories. Furthermore, we provide simulation results that demonstrate improved efficiency enabled by optimal, least norm tension distributions.

We present the Networked InfoMechanical System for Planar Translation, which is a novel two-degree-of-freedom (2-DOF) cable-driven robot with self-calibration and online drift-correction capabilities. This system is intended for actuated sensing applications in aquatic environments. The actuation redundancy resulting from in-plane translation driven by four cables results in an infinite set of tension distributions, thus requiring real-time computation of optimal tension distributions. To this end, we have implemented a highly efficient, iterative linear programming solver, which requires a very small number of iterations to converge to the optimal value. In addition, two novel self-calibration methods have been developed that leverage the robot's actuation redundancy. The first uses an incremental displacement, or jitter method, whereas the second uses variations in cable tensions to determine end-effector location. We also propose a novel least-squares drift-detection algorithm, which enables the robot to detect long-term drift. Combined with self-calibration capabilities, this drift-monitoring algorithm enables long-term autonomous operation. To verify the performance of our algorithms, we have performed extensive experiments in simulation and on a real system.

In this paper, we present a novel linear-program formulation that yields "optimally safe" (OS) tension distributions in parallel cable-driven robots by the introduction of a slack variable. The slack variable also enables explicit computation of a near-optimal, feasible starting point. This, in turn, enables rapid computation of the OS tension distributions. The formulation also contains a parameter that can be used to steer cable tensions toward desired regions of operation. We present static results from two simulated robotic systems that demonstrate the ability of our formulation to avoid tension limits. Simulated execution of highly dynamic trajectories on both systems demonstrates rapid-computation abilities. Furthermore, we present experimental results from a real robotic system that further validate the importance of safe tension distributions.

In this paper we describe an algorithm to generate energy efficient trajectories for NIMS3D, a three-dimensional cabled robotic platform. Optimized parabolic paths are used to exploit the relatively low I2R loss associated with operation in lower regions of the workspace. Trajectory optimization is sufficiently fast to enable real time operation. Experimental results on a physical system for a three cable deployment show substantial reductions in energy consumption as compared to linear trajectories.

As concern for water resource availability increases, so does the need for intelligent aquatic sensing applications. The requirements, and complexity of such applications has also increased due to demands for: 1) broad spatial coverage and high spatial resolution monitoring, 2) capability for resolving fine scale spatiotemporal dynamics and 3) the need for rapid system deployment with semi-autonomous operation. With these criteria in mind, we present the Aquatic Networked InfoMechanical System (NIMS-AQ). NIMS-AQ was developed based on experience gained from engineering research and collaboration with aquatic scientists and environmental engineers during several in-field measurement campaigns [1], [2], [3]. In this paper we demonstrate the effectiveness of NIMS- AQ through two experimental sensing campaigns encompassing both river and lake environments. Each campaign is centered around critical water resource monitoring objectives such as temperature, flow and contaminant levels. Experimental results for autonomous depth profiling using a submersible sonar system as well as adaptive sampling algorithms guided by phenomena models are presented herein. The found results conform with our objectives for rapid and systematic operation. Preliminary studies also indicate the systems viability for use with an autonomous iterative experiment design for environmental applications (A-IDEA) methodology that is currently under development. The IDEA methodology [1] provides effective characterization of spatiotemporal dynamics in aquatic environments. A-IDEA, as it is to be implemented on the NIMS-AQ platform, is also described.

Cabled robotic systems have been used for a diverse set of applications such as environmental sensing, search and rescue, sports and entertainment and air vehicle simulators. In this paper, we introduce a new cabled robot- Networked Info Mechanical System for Planar actuation (NIMS-PL), with energy profiling capabilities. Accurate energy measurements supported by NIMS-PL enable path planning that optimizes the robotpsilas path subject to an upper bound on energy consumption. We performed extensive empirical validation of the optimized path planning approach in simulation using an environmental sensing application as an example. We also validated the simulation results using NIMS-PL, demonstrating significant improvements in the sensing task when accounting with accurate energy measurements as opposed to Euclidean distance, which is typically used for modeling energy spent in path traversal.

Distributed, high-density spatiotemporal observations are proposed for answering many river related questions, including those pertaining to hydraulics and multi-dimensional river modeling, geomorphology, sediment transport and riparian habitat restoration. In spite of the recent advancements in technology, currently available systems have many constraints that preclude long term, remote, autonomous, high resolution monitoring in the real environment. We present here a case study of an autonomous, high resolution robotic spatial mapping of cross-sectional velocity and salt concentration in a river basin. The scientific objective of this investigation was to characterize the transport and mixing phenomena at the confluence of two distinctly different river streams - San Joaquin River and its tributary Merced River. Several experiments for analyzing the spatial and temporal trends at multiple cross-sections of the San Joaquin River were performed during the campaign from August 21-25, 2006. These include deterministic dense raster scans and in-field adapted experimental design. Preliminary analysis from these experiments illustrating the range of investigations is presented with the focus on adaptive experiments that enable sparse sampling to provide larger spatial coverage without discounting the dynamics in the phenomena. Lessons learned during the campaign are discussed to provide useful insights for similar robotic investigations in aquatic environments.

In this paper, we present NIMS RD, a rapidly deployable cable based robotic system developed for environmental monitoring applications. NIMS technology has been under continuous development resulting in several architectures including the NIMS RD system. This is an advance over previous systems in that its operation performance is improved, total system volume and mass is reduced, reliability is increased, and its deployment requires a smaller field team than for previous systems. The NIMS RD design will be described to highlight its new features and innovations. Also, NIMS RD field deployments will be discussed and some of the collected results displayed. Finally, future development directions for the NIMS RD system will also be discussed.

In this paper we present algorithms that enable precise trajectory control of NIMS3D, an underconstrained, three-dimensional cabled robot intended for use in actuated sensing. We begin by offering a brief system overview and then describe methods to determine the range of operation of the robot. Next, a discrete-time model of the system is presented. Thereafter, we present an online algorithm for modeling motor behavior. The majority of the paper is dedicated to describing three feedback control laws used to enable accurate trajectory tracking for both linear and non-linear motion profiles. We present experimental results that highlight the strengths and weaknesses of these mechanisms and conclude by offering a series of future plans for NIMS3D.