Tangle-Free Exploration with a Tethered Mobile Robot

Exploration and remote sensing with mobile robots is a well known field of research, but current solutions cannot be directly applied for tethered robots. In some applications, tethers may be very important to provide power or allow communication with the robot. This paper presents an exploration algorithm that guarantees complete exploration of arbitrary environments within the length constraint of the tether, while keeping the tether tangle-free at all times. While we also propose a generalized algorithm that can be used with several exploration strategies, our implementation uses a modified frontier-based exploration approach, where the robot chooses its next goal in the frontier between explored and unexplored regions of the environment. The basic idea of the algorithm is to keep an estimate of the tether configuration, including length and homotopy, and decide the next robot path based on the difference between the current tether length and the shortest tether length at the next goal position. Our algorithm is provable correct and was tested and evaluated using both simulations and real-world experiments

Exploration of Unknown Environments Using a Tethered Mobile Robot

Exploration with mobile robots is a well known field of research, but current solutions cannot be directly applied for tethered robots. In some applications, tethers may be very important to provide power or allow communication with the robot. This thesis presents an exploration algorithm that guarantees complete exploration of arbitrary environments within the length constraint of the tether, while keeping the tether tangle-free at all times. While a generalized algorithm that can be used with several exploration strategies is also proposed, the presented implementation uses a modified frontier-based exploration approach, where the robot chooses its next goal in the frontier between explored and unexplored regions of the environment. The main modification from standard frontier-based method is the use of a cost function to sort multiple goals in one iteration and pick the cheapest one to go to, minimizing global path length in the process. The cost is calculated in terms of path length with tether constraints accounted for. The basic idea of the algorithm is to keep an estimate of the tether configuration, including length and homotopy, and decide the next robot path based on the length difference between the current tether length and the shortest tether length at the next goal position. The length difference is then used to determine whether it is safe for the robot to take the shortest path to the goal, or whether the robot has to take a different path to the goal in the way that would put the tether back into the most optimal configuration. The maximum length difference that would still guarantee global tangle-free paths has been shown to be the circumference of the smallest expected obstacle in the environment. The presented algorithm is provable correct and was tested and evaluated using both simulations and real-world experiments. Navigation of a planar robot is done with the aid of a Simultaneous Localization and Mapping (SLAM) system, with the data being provided by the on-board LiDAR scanner. The results from conducted experiments have demonstrated that the proposed algorithm results in the total path length increase of anywhere from 30% up to to 80% compared to untethered frontier-based approach, with the exact percentage increase dependent on the complexity of the environment. It is also approximately 6 times shorter than the total path length in a conservative approach of backtracking to the base to avoid tangling

Entanglement Definitions for Tethered Robots: Exploration and Analysis

In this article we consider the problem of tether entanglement for tethered robots. In many applications, such as maintenance of underwater structures, aerial inspection, and underground exploration, tethered robots are often used in place of standalone (i.e., untethered) ones. However, the presence of a tether also introduces the risk for it to get entangled with obstacles present in the environment or with itself. To avoid these situations, a non-entanglement constraint can be considered in the motion planning problem for tethered robots. This constraint can be expressed either as a set of specific tether configurations that must be avoided, or as a quantitative measure of a `level of entanglement' that can be minimized. However, the literature lacks a generally accepted definition of entanglement, with existing definitions being limited and partial. Namely, the existing entanglement definitions either require a taut tether to come into contact with an obstacle or with another tether, or they require for the tether to do a full loop around an obstacle. In practice, this means that the existing definitions do not effectively cover all instances of tether entanglement. Our goal in this article is to bridge this gap and provide new definitions of entanglement, which, together with the existing ones, can be effectively used to qualify the entanglement state of a tethered robot in diverse situations. The new definitions find application mainly in motion planning for tethered robot systems, where they can be used to obtain more safe and robust entanglement-free trajectories. The present article focuses exclusively on the presentation and analysis of the entanglement definitions. The application of the definitions to the motion planning problem is left for future work.Comment: 30 pages, 19 figure

NEPTUNE: Non-Entangling Planning for Multiple Tethered Unmanned Vehicles

Despite recent progress on trajectory planning of multiple robots and path planning of a single tethered robot, planning of multiple tethered robots to reach their individual targets without entanglements remains a challenging problem. In this paper, we present a complete approach to address this problem. Firstly, we propose a multi-robot tether-aware representation of homotopy, using which we can efficiently evaluate the feasibility and safety of a potential path in terms of (1) the cable length required to reach a target following the path, and (2) the risk of entanglements with the cables of other robots. Then, the proposed representation is applied in a decentralized and online planning framework that includes a graph-based kinodynamic trajectory finder and an optimization-based trajectory refinement, to generate entanglement-free, collision-free and dynamically feasible trajectories. The efficiency of the proposed homotopy representation is compared against existing single and multiple tethered robot planning approaches. Simulations with up to 8 UAVs show the effectiveness of the approach in entanglement prevention and its real-time capabilities. Flight experiments using 3 tethered UAVs verify the practicality of the presented approach.Comment: Accepted for publication in IEEE Transaction on Robotic

A Topological Approach to Workspace and Motion Planning for a Cable-controlled Robot in Cluttered Environments

There is a rising demand for multiple-cable controlled robots in stadiums or warehouses due to its low cost, longer operation time, and higher safety standards. In a cluttered environment the cables can wrap around obstacles. Careful choice needs to be made for the initial cable congurations to ensure that the workspace of the robot is optimized. The presence of cables makes it imperative to consider the homotopy classes of the cables both in the design and motion planning problems. In this thesis we study the problem of workspace planning for multiple-cable controlled robots in an environment with polygonal obstacles. This goal of this thesis is to establish a relationship between the workspace\u27s boundary and cable congurations of such robots, and solve related optimization and motion planning problems. We rst analyze the conditions under which a conguration of a cable-controlled robot can be considered valid, then discuss the relationship between cable conguration, the robot\u27s workspace and its motion state, and finally use graph search based motion planning in h-augmented graph to perform workspace optimization and to compute optimal paths for the robot. We demonstrated corresponding algorithms in simulations

Diverse applications of advanced man-telerobot interfaces

Advancements in man-machine interfaces and control technologies used in space telerobotics and teleoperators have potential application wherever human operators need to manipulate multi-dimensional spatial relationships. Bilateral six degree-of-freedom position and force cues exchanged between the user and a complex system can broaden and improve the effectiveness of several diverse man-machine interfaces

Motion Planning for a Tethered Mobile Robot

Recently there has been surge of research in motion planning for tethered robots. In this problem a planar robot is connected via a cable of limited length to a fixed point in R2. The configuration space in this problem is more complicated than the one of a classic motion planning problem as existence of the cable causes additional constraints on the motion of the robot. In this thesis we are interested in finding a concise representation of the configuration space that results in a straightforward planning algorithm. To achieve such a representation we observe that configuration space manifold has a discrete structure that conveniently can be separated from its continuous aspect when it is represented as an atlas of charts. We provide a method for generating either the complete atlas or a subset of its charts based on special cable events. Generating parts of the configuration space on-the-fly enables the following improvements over the state-of-the-art. a) We decompose the environment into cells as needed rather than an off-line global discretization, obtaining competitive time and space complexity for our planner. b) We are able to exploit topological structure to represent robot-cable configurations concisely leading us towards solutions to the more complex problems of interest. To underscore the potential of this representation, we take further steps to generalize it to two more complicated instances of the tethered robot planning problem that has been widely disregarded in the literature. We will first consider a simplified model of cable-to-cable contacts, giving the robot the option to perform knot-like tying motions. Next, we will address the planning problem for a tethered robot whose cable has a constraint on its curvature. This adds to the realism of the model since most practical cables have some degree of stiffness which limits curvature. In this case we provide a novel technique to relate Dubins' theory of curves with work on planning with topological constraints. Our results show the efficiency of the method and indicate further promise for procedures that represent manifolds via an amalgamation of implicit discrete topological structure and explicit Euclidean cells