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Snake robots have shown limited ability to perform manipulation tasks in comparison to their locomotion capabilities. In this article, we propose a mobile manipulation approach that increases the manipulation ability of snake robots by using their full-body motion. We consider a snake robot that moves along the outer surface of a pipe using the helical rolling gait. To perform a manipulation task, we extend the front links of the robot to form a manipulator-part, where the remaining links form a helical base that wraps around the pipe. In the proposed approach, the motion of the manipulator-part is combined with a rolling motion performed by the base-part. This results in enhanced rotational ability of the end-effector, without the need to install an additional rotary motor. The stability of the robot structure is also improved via the resulting tightening force between the helical base-part and the pipe. The kinematics of the proposed robot arrangement is represented considering a dynamically changing contact point between the links of the helical base and the pipe. To realize the proposed method, we introduce a two-level controller that enables the manipulator-part and the helical base to work simultaneously during manipulation. The experimental results showed the validity of the proposed method to track various trajectories and carry out manipulation tasks using a typical snake robot without extra actuators.

Several methods have been developed in recent years to automatically design cable paths for a given robot motion. However, an optimal solution may not be found when applied to complex motions such as inspection or assembly processes. Observation of experts’ works reveals that multiple guides are empirically fixed on one link to avoid cable collisions with peripheral devices and to lessen cable bending fatigue. This study proposes a cable path optimization method with multiple guides on one link to obtain the optimal solution for complex motions. Further, it experimentally demonstrates its effectiveness. However, fixing multiple guides on one link may increase computational burden because the solution search space will remarkably expand. Therefore, a combination of Hermite interpolation and interpolated coordinate system calculation using rotation minimizing frames was introduced to reduce the significant burden of connected geometry computation. The connected geometry is the geometry of the cable segment which connects the guides at both ends and is used as an initial geometry in the physical simulation considering gravity to determine the convergent geometry of the cable segment.

This article studies the min-consensus control of continuous-time real-valued multiagent systems, with sampled information, quantized communication, and switching topologies. Due to the limited bandwidth of the digital communication network, only finite-bit binary symbolic sequence can be exchanged among the agents. In order to realize the min-consensus control with quantized communication and limited bandwidth, a novel finite-level biased quantizer and a nonstrict decreasing scaling function are designed, and correspondingly a set of switching encoders and decoders are constructed. By means of the proposed encoders and decoders, the according sampled-data min-consensus control inputs are carefully constructed, and the memory variables are introduced into the control inputs and are monotonically decreasing no matter how the communication topology is switched. The proposed encoding-decoding-based control scheme can achieve accurate min-consensus with limited bandwidth, as long as the communication graphs are jointly strongly connected. The numerical simulations show the effectiveness of the proposed control scheme.

Path integral policy improvement (PI^2) is known to be an efficient reinforcement learning algorithm, particularly, if the target system is a high-dimensional dynamical system. However, PI^2 , and its existing extensions, have adjustable parameters, on which the efficiency depends significantly. This article proposes an extension of PI^2 that adjusts all of the critical parameters automatically. Motion acquisition tasks for three different types of simulated legged robots were performed to test the efficacy of the proposed algorithm. The results show that the proposed method cannot only eliminate the burden on the user to set the parameters appropriately but also improve the optimization performance significantly. For one of the acquired motions, a real robot experiment was conducted to show the validity of the motion.

We propose a new simplified model for the control design of snake robots and apply it to a path-following control design using model predictive control (MPC). While MPC has an advantage in that inequality constraints can be explicitly considered in control design, most of the previous simplified models are still too complex to apply to MPC since the models include joint angles as time-varying parameters. Thus, we exclude joint angles using the averaging method to construct a simpler model. Another feature of the proposed model is that it can be derived from the original complex model without parameter identification using simulation data and without assuming straight-line movements. In addition to inequality constraints on joint angles and the frequency of joint motions, we impose constraints on the change rates of these variables in our MPC design since the averaged model is derived by assuming that these variables slowly change. Furthermore, we introduce a soft constraint to decrease the effects of approximation error of the simplified model on the control performance. The effectiveness of the control system is verified in both simulations and experiments.

A snake robot performs diverse motions. To realize a wide range functions in a complex environment, it is necessary to transition between various motions suited to each environment. In this article, we propose a method of transitioning the motion of a snake robot across different environments to expand the application environment of the robot. We first find that the motion at the connection point between two motions must coincide with the tangential movement during motion transition across different environments. We then design a gait called the circular pedal wave. This circular pedal wave allows a hoop-passing motion in which the whole body moves as if it is passing through a virtual hoop fixed in space in sequence from its head through combination with a proposed shift part. The hoop-passing motion allows motion transition across different environments. We propose three application examples of this hoop-passing motion, namely passing through a hole in a wall, entering an underfloor, and attaching to a ladder. We report on experiments conducted to verify the effectiveness of the proposed method and to realize the described motions.

Point cloud information is a convenient means to accomplish grasp detection in autonomous robotic grasping. However, the performance of various state-of-the-art grasp detection methods that use poi...

This paper proposes a method to improve the tactile sensitivity of the fingertip by placing multiple vibrators at a remote position away from the fingertip. It is known that a fingertip's tactile sensitivity improves when vibrotactile noise is applied to the fingertip or to a position away from the fingertip, such as the wrist. This is the application of stochastic resonance to the field of haptics. Preliminary experiments in this study have shown that the improvement of a fingertip's tactile sensitivity via remote vibrotactile noise depends on the propagation of the vibration on human skin. From the results of the preliminary experiments, it is expected that the larger the noise reaching the fingertip, the smaller the detectable input. Therefore, we consider that multiple vibrators at a remote position can propagate a larger noise to the fingertip and further improve the fingertip's tactile sensitivity compared to the use of only one vibrator as occurred in a previous study. Finite element analysis was performed so that the noises from multiple vibrators were properly superimposed at the fingertip. To synchronize the arrival of the noises at the fingertip from the multiple vibrators, we determined the positions of the vibrators and the time when each vibrator started generating noise. The results of a subject experiment confirmed that the proposed method significantly improved fingertip sensitivity compared to the case without SR or the case where only one vibrator was used.

In the field of unmanned aerial vehicles (UAVs), aerial manipulations are receiving considerable attention because of their potential application to tasks such as pick and place, detection, and inspection. However, short flight endurance times and concerns about the safety to surroundings during interacting heavily limit the expansion of aerial manipulations in real implementations. To overcome these challenges, this paper focuses on a system in which a quadrotor UAV is equipped with a lightweight and flexible arm. Based on the infinite-dimensional dynamics, the mathematic model of system is described by a hybrid partial differential equation-ordinary differential equation (PDE-ODE). An easily implementable controller is derived from a Lyapunov functional construction related to the energy of the system. The proposed controller ensures global Lyapunov stability for nonlinear system and local asymptotic stability for the linearized system. Further, it is shown that the proposed controller realizes stable motion of the aerial manipulator as well as vibration control of the flexible arm. Finally, numerical simulations are conducted to investigate the validity of the proposed controller.

This paper discusses a grasping, orientation, and position control of an object by two flexible arms modeled by the Timoshenko beam. By utilizing our previously proposed controller for the cooperative control, we realize to control the grasping force, orientation, and position of an object as well as to suppress the vibration of the flexible arms. In particular, the closed-loop system is formulated in a Hilbert space, and the exponential stability of the closed-loop system is shown by the frequency domain method. The lightweight flexible arm has intrinsic elastic compliance, and thus the grasping by the flexible arms is safer than that by the rigid arms. In addition, the exponential stability of the closed-loop system contributes to the performance improvement of the grasping and manipulation of an object. Finally, experiments are conducted to confirm the validity of the stability analysis.

Minimally invasive surgery is a useful but challenging surgical technique. Several robotic manipulators have been realized in the past three decades to overcome its difficulties. However, a majority of these manipulators lack two important features. First, the ability to provide a right-angled tool entry (with respect to the surrounding skin tissue) for entry-ports located on the far-side of the patient's body, and second, rapid change of the surgical tools. To solve these issues, this article presents synthesis of a new surgical manipulator that ensures a right-angled tool entry—in order to reduce postoperative pain in the patient's skin tissue—through its novel design. We describe the design, perform kinematic analysis, and validate the robotic manipulator's ability to maintain a remote center of motion. The proposed manipulator is equipped with a quick-release mechanism to facilitate rapid change of the surgical instruments during robot-assisted surgery. Contrary to the state-of-the-art, the proposed manipulator does not require extra passive arms to provide a proper tool entry-angle. The manipulator's performance is experimentally evaluated by performing tool-insertion, pegs-transfer, and path-following tasks in a master–slave teleoperation setting. It is demonstrated that the manipulator can perform basic surgical tasks, such as pick-and-place and object manipulation, with a high success rate.

To learn motor skills using a finger in many haptic training systems, a user places his or her finger in a holder to communicate with a haptic interface. It is known that the force-detection capability at the fingertip is reduced when the user's finger is enclosed in a holder. The learning performance might therefore be impaired in training. Stochastic resonance is known to improve sensitivity at the fingertip. We thus propose a fingertip force learning method using stochastic resonance. We first examine the effect of stochastic resonance on the user haptic performance in a two-dimensional task when the fingertip is within the finger holder. The outcomes indicate that the user fingertip sensitivity increases even when the finger is placed within a holder. We next perform force learning tasks in one- and two-dimensional space. Our proposed method that combines haptic feedback and stochastic resonance is compared with the method in which only haptic feedback is provided to the user in force leaning tasks. Results obtained using the proposed method indicate that the performance outcome of the proposed method is higher than that of the comparison method. This study demonstrates the potential of the proposed method for motor learning tasks.

This paper presents a stability analysis of swarm robots, a group of multiple robots. In particular, we focus on robot swarms with heterogeneous abilities, in which each robot has a different sensing range and physical limitations, including maximum velocity and acceleration. In addition, each robot has a unique sensing region with a limited angle field of view. We previously proposed a decentralized navigation method for such heterogeneous swarm robots consisting of one leader and multiple followers. With the decentralized navigation method, a single leader can navigate for followers while maintaining connectivity and satisfying the physical limitations unique to each robot; i.e., each follower has a target robot and follows it without violating its physical limitations. In this paper, we focus on a stability analysis of such swarm robots. When the leader moves at a constant velocity, we mathematically prove that the shape and orientations of all robots eventually converge to the equilibrium state. For this, we must first prove that the equilibrium state exists. Then, we show the convergence of the state to its equilibrium. Finally, we carry out experiments and numerical simulations to confirm the stability analysis, i.e., the convergence of the swarm robots to the equilibrium states.

Snake robots are capable of adapting to difficult situations, such as cluttered environments, using its many degrees of freedom. However, if one of the joints gets passive, it is generally very difficult to achieve ordinary performance. In this paper, control of a passive joint using rolling motion is considered, with the use of crawler gait in mind. Crawler gait is a state-of-the-art motion pattern for snake robots that is capable of moving on uneven terrain, but if there is a passive joint, the motion can be interrupted by freely moving part of the robot itself. As a key to solving this difficulty, this paper proposes to use the rolling motion, which has not been used in controlling a passive joint. A simplified model is proposed to consider the control, and based on this, one simple controller is adopted. The validity of the idea of using rolling motion is tested by numerical simulations.

To date, many gait generation strategies have been designed for robots with leg configurations that model those of natural creatures. However, their leg configurations are limited to the $2\times N$ type, such as hexapod or myriapod; hence, simultaneously, the potential ability of legged robots is implicitly limited. We consider single-legged modular robots that can be arranged to form a cluster with arbitrary 2-D leg configurations. By choosing configurations appropriately, these robots have the potential to perform several types of tasks, as is the case for reconfigurable modular robots. However, to use appropriate configurations for a given task, a unified gait generation system for various configurations of a cluster is required. In this article, we propose an autonomous distributed control system for each single-legged modular robot to collectively achieve static walking of the cluster with various leg configurations on planar ground. Moreover, our system is an autonomous distributed system with scalability and fault tolerance, in which each module determines the moving pattern of its foot through local communication without global information, such as the entire leg configuration of the cluster. We verified that several types of clusters achieved static walking using our system not only in dynamic simulations, but also in real robot experiments.

In this paper, we consider autonomous navigation of a wheeled mobile robot in a dynamic environment using a 3D point cloud map. We consider four kinds of 2D maps: static global map, dynamic global map, global cost map, and local cost map; to plan a feasible path of the robot to adapt to a dynamic environment. We consider a mobile robot for plant patrolling in a 3D environment with plane slopes but not rough terrain for which a 2D environment map suffices. We propose 2D static global map for robot navigation by projecting prior measured 3D point cloud map data on a horizontal plane with considering the climbing ability of the robot. We also build a 2D dynamic global map by projecting a real-time 3D point cloud on the 2D static global map by SLAM. Accumulated errors of SLAM can be canceled using some landmarks placed in the environment. A global planner calculates an optimal global path that minimizes the distance from an initial robot pose (position and orientation) to a goal pose (position and orientation) by A* algorithm based on the global cost map which is built from the dynamic global map. However, this process should take much time. To avoid moving obstacles, the TEB (Timed Elastic Band) local planner is used to calculate an optimal local path based on a local cost map which is given by a real-time local 3D point cloud. To demonstrate the effectiveness of the proposed system, experiments were carried out. In the experiment, we use an AR card as a landmark for simplification of implementation. We prove that the robot can navigate in a dynamic environment and accumulated errors can be canceled by the AR cards placed in the environment as landmarks.

We address a cooperative transport control problem involving three or more unmanned aerial vehicles (UAVs). We realize the transportation of an object that cannot be carried with a small number of UAVs. To improve scalability and real-time performance, we propose a controller that does not require optimization calculations. The attitude and position of the transported object are controlled by contact forces with the UAVs. The control system comprises two steps in which (1) a force is allocated to each UAV and (2) UAVs realize the force allocation using a decentralized disturbance observer-based controller. A friction cone constraint related to static friction is considered using the redundant degree of freedom in the force allocation. The effectiveness of the controller is verified in numerical simulations.

This paper deals with contact-force control of a one-link flexible arm whose tip is constrained to a rigid environment. To realize the contact-force control, a boundary controller is proposed based on a dynamic model represented by an infinite dimensional model. In particular, the proposed controller does not need the physical parameters in its implementation, and this results in the non-collocated boundary controller. The closed-loop system is analyzed in an appropriate Hilbert space, and it is shown that the exponential stability of the closed-loop system is obtained by setting the feedback gains to locate the eigenvalues of the closed-loop system on the complex left half-plane. In addition, in an attempt to realize the better control performance, another controller which is a modified version of our controller is proposed. Finally, the stability, robustness to the uncertainty in physical parameters, and disturbance response of the closed-loop system are investigated by numerical simulations.

Horses use the transverse gallop in high-speed running. However, different animals use different gaits, and the gait preference of horses remains largely unclear. Horses have fore-aft asymmetry in their body structure and their center of mass (CoM) is anteriorly located far from the center of the body. Since such a CoM offset affects the running dynamics, we hypothesize that the CoM offset of horses is important in gait selection. In order to verify our hypothesis and clarify the gait selection mechanisms by horses from a dynamic viewpoint, we developed a simple model with CoM offset and investigated its effects on running. Specifically, we numerically obtained periodic solutions and classified these solutions into six types of gaits, including the transverse gallop, based on the footfall pattern. Our results show that the transverse gallop is optimal when the CoM offset is located at the position estimated in horses. Our findings provide useful insight into the gait selection mechanisms in high-speed running of horses.

Quadrupedal mammals have fore-aft asymmetry in their body structure, which affects their walking and running dynamics. However, the effects of asymmetry, particularly in the transverse plane, remain largely unclear. In this study, we examined the effects of fore-aft asymmetry on quadrupedal trotting in the transverse plane from a dynamic viewpoint using a simple model, which consists of two rigid bodies connected by a torsional joint with a torsional spring and four spring legs. Specifically, we introduced fore-aft asymmetry into the model by changing the physical parameters between the fore and hind parts of the model based on dogs, which have a short neck, and horses, which have a long neck. We numerically searched the periodic solutions for trotting and investigated the obtained solutions and their stability. We found that three types of periodic solutions with different foot patterns appeared that depended on the asymmetry. Additionally, the asymmetry improved gait stability. Our findings improve our understanding of gait dynamics in quadrupeds with fore-aft asymmetry.

Multi-legged animals show several types of ipsilateral interlimb coordination. Millipedes use a direct-wave gait, in which the swing leg movements propagate from posterior to anterior. In contrast, centipedes use a retrograde-wave gait, in which the swing leg movements propagate from anterior to posterior. Interestingly, when millipedes walk in a specific way, both direct and retrograde waves of the swing leg movements appear with the waves' source, which we call the source-wave gait. However, the gait generation mechanism is still unclear because of the complex nature of the interaction between neural control and dynamic body systems. The present study used a simple model to understand the mechanism better, primarily how local sensory feedback affects multi-legged locomotion. The model comprises a multi-legged body and its locomotion control system using biologically inspired oscillators with local sensory feedback, phase resetting. Each oscillator controls each leg independently. Our simulation produced the above three types of animal gaits. These gaits are not predesigned but emerge through the interaction between the neural control and dynamic body systems through sensory feedback (embodied sensorimotor interaction) in a decentralized manner. The analytical description of these gaits' solution and stability clarifies the embodied sensorimotor interaction's functional roles in the interlimb coordination.

We present the design of a new hand-grounded semi-flexible kinesthetic haptic device, which aims to be fully-compatible to the needs of Robot-Assisted Surgeries (RAS).

Robots are needed in rescue activities and the inspection of infrastructure. We developed the rescue robot FUHGA2 so that it has various functions. FUHGA2 has high mobility, with main crawlers cove...

The stability of two one-link flexible arms for grasping and orientation control of an object is studied. Flexible arms are modelled by Euler–Bernoulli beam model and the overall system is represented by a hybrid partial differential equation (PDE)–ordinary differential equation (ODE) model. The authors' primary concern is the stability analysis of this hybrid PDE–ODE model. In particular, they use the frequency domain method and prove the exponential stability of this system under their previously proposed boundary controller. In addition, they discuss the robustness of the closed-loop system with respect to the several disturbances including disturbances distributed over the arms and disturbances acting at boundaries. Finally, simulation results are presented to investigate the theoretical results.

In the field of aerial robotics, physical interaction with the surrounding environment is currently receiving a considerable attention. One of the key challenges is to control not only the position, but also the force exerted by the end-effector while performing complex tasks such as object manipulation, inspection, and assembly/disassembly. To meet these demands, this paper proposes a dynamic hybrid position/force controller for a quadrotor-borne multi-degree-of-freedom manipulator. The system is modeled under the situation that the constraints on the end-effector are described by a set of hypersurfaces, and system dynamics are then developed while taking into account the redundancy of the system. To verify the effectiveness of the proposed hybrid controller, we carried out numerical simulations for two different application scenarios which include (1) placement of a sensor unit on a vertical wall and (2) inspection with contact on a curved-shape wall. The results show that the system is able to maintain the desired force and position simultaneously in both cases.