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In this article, we consider the problem of mass transport cloaking using mobile robots. The robots move along a predefined curve that encloses a safe zone and carry sources that collectively counteract a chemical agent released in the environment. The goal is to steer the mass flux around a desired region so that it remains unaffected by the external concentration. We formulate the problem of controlling the robot positions and release rates as a partial differential equation (PDE)-constrained optimization, where the propagation of the chemical is modeled by the advection-diffusion (AD) PDE. We use a neural network (NN) to approximate the solution of the PDE. Particularly, we propose a novel loss function for the NN that utilizes the variational form of the AD-PDE and allows us to reformulate the planning problem as an unsupervised model-based learning problem. Our loss function is discretization-free and highly parallelizable. Unlike passive cloaking methods that use metamaterials to steer the mass flux, our method is the first to use mobile robots to actively control the concentration levels and create safe zones independent of environmental conditions. We demonstrate the performance of our method in simulations. [ABSTRACT FROM AUTHOR]

In this paper, we propose a control method, providing mobile robots with whole-body compliance capabilities, in response to multicontact physical interactions with their environment. The external forces applied to the robot, as well as their localization on its kinematic tree, are measured using a multimodal, self-configuring, and self-calibrating artificial skin. We formulate a compliance control law in Cartesian space, as a set of quadratic optimization problems, solved in parallel for each limb involved in the interaction process. This specific formulation makes it possible to determine the torque commands required to generate the desired reactive behaviors, while taking the robot kinematic and dynamic constraints into account. When a given limb fails to produce the desired compliant behavior, the generalized force residual at the considered contact points is propagated to a parent limb in order to be adequately compensated. Hence, the robot's compliance range can be extended in a both robust and easily adjustable manner. The experiments performed on a dual-arm velocity-controlled mobile manipulator show that our methodology is robust to nullspace interactions and robot physical constraints. [ABSTRACT FROM AUTHOR]

Helical microswimmers that are capable of propulsion at low Reynolds numbers have great potential for numerous applications. Several kinds of artificial magnetic-actuated helical microswimmers have been designed by researchers. However, they are primarily open-loop controlled. This paper aims to investigate methods of closed-loop control of a magnetic-actuated helical swimmer at low Reynolds number by using visual feedback. For many in-vitro applications, helical swimmers should pass through a defined path, for example along channels with no prerequisite on the velocity profile along the path. Therefore, the main objective of this paper is to achieve a velocity-independent planar path following task. Since the planar path following is based on 3-D steering control of the helical swimmer, a 3-D pose estimation of a helical swimmer is introduced based on the real-time visual tracking with a stereo vision system. The contribution of this paper is in two parts: The 3-D steering of a helical swimmer is demonstrated by visual servo control; and the path following of a straight line with visual servo control is achieved, then compared with open-loop control. We further expect that with this visual servo control method, the helical swimmers will be able to follow reference paths at the microscale. [ABSTRACT FROM PUBLISHER]

This paper presents “1STAR,” which is the first robot that is driven by a single actuator but can be directly commanded to move straight or turn clockwise or counterclockwise. The legged robot relies on a novel actuation gait, which exploits the compliance disparity between alternate stance tripods, to generate rotation by continuously accelerating and decelerating the legs. The direction of turning depends on the configuration of the legs—tripod left or right—and the timing of the acceleration and deceleration. Alternating leg acceleration in successive steps allows for continuous rotation in the desired direction. The turning radius can be varied by changing the timing of the leg acceleration and deceleration without changing the cycle frequency and linear speed. A simplified kinematic motion model of a robot is presented, and a dynamic simulation is performed to analyze the behavior and optimize robot parameters. The locomotion gait is verified experimentally using our newly designed “1STAR” robot. [ABSTRACT FROM PUBLISHER]

Driving mobile robots to precise locations is of recognized interest, and using vision sensors in this context supplies many advantages. We propose a novel control law based on sliding-mode theory in order to drive mobile robots to a target location, which is specified by a previously acquired reference image. The control scheme exploits the piecewise epipolar geometry of three views on the basis of image-based visual servoing, in such a way that no 3-D scene information is required. The contribution of the paper is a new control law that achieves convergence to the target with no auxiliary images and without changing to any approach other than epipolar-based control. Additionally, the use of sliding-mode control deals with singularities, thus allowing the robot to move directly toward the target as well as avoiding the need of a precise camera calibration. The effectiveness of our approach is tested with simulations and real-world experiments. [ABSTRACT FROM AUTHOR]

For a compass-like biped robot, the problem of achieving stable walking on both ideal inclined surfaces and complex environments is studied. For the case of walking on ideal inclined surfaces, a feedback-control law is obtained via feedback-linearization techniques so that the trajectory of the robot converges to a desired passive walking gait. Simulations show that it leads to a larger basin of attraction. For the case of walking in complex environments, a scheme is developed with regulable step length and walking speed. Different reference trajectories are constructed for different steps, and corresponding feedback-control laws are updated at the beginning of each step. Then, it is shown that the errors that measure the difference of the response trajectory and the reference one asymptotically converge to zero. An example of walking over stairs is given to numerically verify and demonstrate our approach. [ABSTRACT FROM AUTHOR]

Consider a biped evolving in the sagittal plane. The unexpected rotation of the supporting foot can be avoided by controlling the zero moment point (ZMP). The objective of this study is to propose and analyze a control strategy for simultaneously regulating the position of the ZMP and the joints of the robot. If the tracking requirements were posed in the time domain, the problem would be underactuated in the sense that the number of inputs would be less than the number of outputs. To get around this issue, the proposed controller is based on a path-following control strategy, previously developed for dealing with the underactuation present in planar robots without actuated ankles. In particular, the control law is defined in such a way that only the kinematic evolution of the robot's state is regulated, but not its temporal evolution. The asymptotic temporal evolution of the robot is completely defined through a one degree-of-freedom subsystem of the closed-loop model. Since the ZMP is controlled, bipedal walking that includes a prescribed rotation of the foot about the toe can also be considered. Simple analytical conditions are deduced that guarantee the existence of a periodic motion and the convergence toward this motion. [ABSTRACT FROM AUTHOR]

We consider the problem of approximating a finite-length continuous curve by a piecewise linear one whose segments are assumed to be connected by 2 DOE joints. We solve the problem under the assumption that the endpoints of the line segments lie on the continuous curve. Analytical expressions for the relative orientations of each pair of line segments as a function of a single rotational DOE are found. This angle can be chosen arbitrarily or used to optimize a secondary task. The motivating application for this paper is the control of a snake-like robot using gaits designed from shape primitives. [ABSTRACT FROM AUTHOR]

In formation-maintenance (formation control) tasks, robots maintain their relative position with respect to their peers, according to a desired geometric shape. Previous work has examined formation-maintenance algorithms, based on formation control graphs, that ensure the theoretical stability of the formation. However, an exponential number of stable controllers exists. Thus a key question is how to select (construct) a formation controller that optimizes desired properties, such as sensor usage. We present a novel representation of the sensing capabilities of robots in formations, using a monitoring multigraph. We first show that graph-theoretic techniques can then be used to efficiently compute optimal sensing policies that maintain a given formation, while minimizing sensing costs. In particular, separation-bearing (distance-angle) control targets are automatically constructed for each individual robot in the formation, taking into account its specific sensor morphology. Then, we present a protocol allowing control graphs to be switched on line, to allow robots to adjust to sensory failures. We report on results from comprehensive experiments with physical and simulated robots. The results show that the use of the dynamic protocol allows formations of real robots to move significantly faster and with greater precision, while reducing the number of formation failures, due to sensor limitations. We also evaluate the sensitivity of our approach to communication reliability, and discuss opportunities and challenges raised by our approach. [ABSTRACT FROM AUTHOR]

Mobile robots can be used in many applications, such as carpet cleaning, search and rescue, and exploration. Many studies have been devoted to the control, sensing, and communication of robots. However, the deployment of robots has not been fully addressed. The deployment problem is to determine the number of groups unloaded by a carrier, the number of robots in each group, and the initial locations of those robots. This paper investigates robot deployment for coverage tasks. Both timing and energy constraints are considered; the robots carry limited energy and need to finish the tasks before deadlines. We build power models for mobile robots and calculate the robots' power consumption at different speeds. A speed-management method is proposed to decide the traveling speeds to maximize the traveling distance under both energy and timing constraints. Our method uses rectangle scanlines as the coverage routes, and solves the deployment problem using fewer robots. Finally, we provide an approach to consider areas with random obstacles. Compared with two simple heuristics, our solution uses 36% fewer robots for open areas and 32% fewer robots for areas with obstacles. [ABSTRACT FROM AUTHOR]