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This paper presents a method for designing the gait of a snake robot that moves in a complicated environment. We propose a method for expressing the target form of a snake robot by connecting curve segments whose curvature and torsion are already known. Because the characteristics of each combined shape are clear, we can design the target form intuitively and approximate a snake robot configuration to this form with low computational cost. In addition, we propose two novel gaits for the snake robot as a design example of the proposed method. The first gait is aimed at moving over a flange on a pipe, while the other is the crawler gait aimed at moving over rough terrain. We demonstrated the effectiveness of the two gaits on a pipe and rough terrain in 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]

We propose nonholonomic passive decomposition, which enables us to decompose the Lagrange–D’Alembert dynamics of multiple (or a single) nonholonomic mechanical systems with a formation-specifying (holonomic) map h into 1) shape system, describing the dynamics of h(q) (i.e., formation aspect), where q \in \Re^n is the systems’ configuration; 2) locked system, describing the systems’ motion on the level set of h with the formation aspect h(q) being fixed (i.e., maneuver aspect); 3) quotient system, whose nonzero motion perturbs both the formation and maneuver aspects simultaneously; and 4) energetically conservative inertia-induced coupling among them. All the locked, shape, and quotient systems individually inherit Lagrangian dynamics-like structure and passivity, which facilitate their control design/analysis. Canceling out the coupling, regulating the quotient system, and controlling the locked and shape systems individually, we can drive the formation and maneuver aspects simultaneously and separately. Notions of formation/maneuver decoupled controllability are introduced to address limitations imposed by the nonholonomic constraint, along with passivity-based formation/maneuver control design examples. Numerical simulations are performed to illustrate the theory. Extension to kinematic nonholonomic systems is also presented. [ABSTRACT FROM AUTHOR]

To efficiently solve challenges related to motion-planning problems with dynamics, this paper proposes treating motion planning not just as a search problem in a continuous space but as a search problem in a hybrid space consisting of discrete and continuous components. A multilayered framework is presented which combines discrete search and sampling-based motion planning. This framework is called synergistic combination of layers of planning (SyCLoP) hereafter. Discrete search uses a workspace decomposition to compute leads, i.e., sequences of regions in the neighborhood that guide sampling-based motion planning during the state-space exploration. In return, information gathered by motion planning, such as progress made, is fed back to the discrete search. This combination allows SyCLoP to identify new directions to lead the exploration toward the goal, making it possible to efficiently find solutions, even when other planners get stuck. Simulation experiments with dynamical models of ground and flying vehicles demonstrate that the combination of discrete search and motion planning in SyCLoP offers significant advantages. In fact, speedups of up to two orders of magnitude were obtained for all the sampling-based motion planners used as the continuous layer of SyCLoP. [ABSTRACT FROM AUTHOR]

As robots come closer to humans, an efficient human-robot-control interface is an utmost necessity. In this paper, electromyographic (EMG) signals from muscles of the human upper limb are used as the control interface between the user and a robot arm. A mathematical model is trained to decode upper limb motion from EMG recordings, using a dimensionality-reduction technique that represents muscle synergies and motion primitives. It is shown that a 2-D embedding of muscle activations can be decoded to a continuous profile of arm motion representation in the 3-D Cartesian space, embedded in a 2-D space. The system is used for the continuous control of a robot arm, using only EMG signals from the upper limb. The accuracy of the method is assessed through real-time experiments, including random arm motions. [ABSTRACT FROM AUTHOR]

The admittance of a manipulator can be used to improve robotic assembly. If properly selected, the admittance will regulate a contact force and use it to guide the parts to proper positioning. In previous work, procedures for selecting the appropriate admittance for single principal contact (PC) cases were identified. This paper extends this research for some of the two PC cases—those for which each contact occurs at a single point. The conditions obtained ensure that the motion that results from frictionless contact always instantaneously reduces part misalignment. We show that, for bounded misalignments, if an admittance satisfies the misalignment. reducing conditions at a finite number of contact configurations, then the admittance will also satisfy the conditions at all intermediate configurations. [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 this paper, a novel type of impedance controllers for flexible joint robots is proposed. As a target impedance, a desired stiffness and damping are considered without inertia shaping. For this problem, two controllers of different complexity are proposed. Both have a cascaded structure with an inner torque feedback loop and an outer impedance controller. For the torque feedback, a physical interpretation as a scaling of the motor inertia is given, which allows to incorporate the torque feedback into a passivity-based analysis. The outer impedance control law is then designed differently for the two controllers. In the first approach, the stiffness and damping terms and the gravity compensation term are designed separately. This outer control loop uses only the motor position and velocity, but no noncollocated feedback of the joint torques or link side positions. In combination with the physical interpretation of torque feedback, this allows us to give a proof of the asymptotic stability of the closed-loop system based on the passivity proper- ties of the system. The second control law is a refinement of this approach, in which the gravity compensation and the stiffness implementation are designed in a combined way. Thereby, a desired static stiffness relationship is obtained exactly. Additionally, some extensions of the controller to viscoelastic joints and to Cartesian impedance control are given. Finally, some experiments with the German Aerospace Center (DLR) lightweight robots verify the developed controllers and show the efficiency of the proposed control approach. [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]