This paper presents the kinematics of a planar multibody vehicle which is aimed at the exploration, data collection, non-destructive testing and general autonomous navigation and operations in confined environments such as pipelines. The robot is made of several identical modules hinged by passive revolute joints. Every module is actuated with four active revolute joints and can be regarded as a parallel mechanism on a mobile platform. The proposed kinematics allows to overcome the nonholonomic kinematic constraint, which characterizes typical wheeled robots, resulting into a higher number of degrees of freedom and therefore augmented actuation inputs. Singularities in the kinematics of the modules are analytically identified. We present the dimensional synthesis of the length of the arms obtained as the solution of an optimization problem with respect to a suitable dexterity index. Simulation results illustrate a kinematic control path following inside pipes. Critical scenarios such as 135° elbows and concentric restriction are explored. Path following shows the kinematic capability of deployment of the robot for autonomous operations in pipelines, with feedback implemented by on-board sensors.

In this paper, a new flexure-based micropositioning stage (FMPS) is proposed to achieve decoupled XY translational motions and large travel ranges. The stage consists of four independent kinematic chains, each comprising two flexure-beam prismatic joints. The mechanism with such a special topological structure enables the motions of the platform strictly along XY axes and minimizes the parasitic rotation in theta axis. The kinematics and dynamics analysis of the mechanism are conducted to evaluate the performance of the mechanism in terms of travel range, parasitic motions, linearity, as well as natural frequency. According to the developed models, a parameter optimization of the mechanism is performed under the condition of the maximum travel range. The finite element simulation is carried out to examine the mechanical performance and the theoretical models. The experimental results show that the proposed FMPS possesses a workspace of 600 × 600 μm2, a relative coupling error of 0.6%, and the natural frequencies of 209.7 Hz and 212.4 Hz for the first two modes.

A brain–computer interface (BCI) is a system for commanding a device by means of brain signals without having to move any muscle. One kind of BCI is based on Steady-State Visual Evoked Potentials (SSVEP), which are evoked visual cortex responses elicited by a twinkling light source. Stimuli can produce visual fatigue; however, it has been well established that high-frequency SSVEP (>30 Hz) does not. In this paper, a mobile robot is remotely navigated into an office environment by means of an asynchronous high-frequency SSVEP-based BCI along with the image of a video camera. This BCI uses only three electroencephalographic channels and a simple processing signal method. The robot velocity control and the avoidance obstacle algorithms are also herein described. Seven volunteers were able to drive the mobile robot towards two different places. They had to evade desks and shelves, pass through a doorway and navigate in a corridor. The system was designed so as to allow the subject to move about without restrictions, since he/she had full robot movement's control. It was concluded that the developed system allows for remote mobile robot navigation in real indoor environments using brain signals. The proposed system is easy to use and does not require any special training. The user's visual fatigue is reduced because high-frequency stimulation is employed and, furthermore, the user gazes at the stimulus only when a command must be sent to the robot.

This work aims to propose an innovative mechanism of human–robot collaboration (HRC) for mobile service robots in the application of elderly and disabled assistance. Previous studies on HRC mechanism usually focused on integrating decision-making intelligence of human beings by qualitative judgment and reasoning intelligence of robots by quantitative calculation. Instead, novelties of the proposed methodology include (1) constructing an HRC framework by taking reference from the Adaptive Control of Thought – Rational (ACT-R) human cognitive architecture; (2) establishing semantic webs of cognitive reasoning through human–robot interaction (HRI) and HRC to plan and implement complex tasks; and (3) realizing human–robot intelligence fusion by mutual encouragement, connect, and integration of modules of human, robot, perception, HRI, and HRC in the ACT-R architecture. Its technical feasibility is validated by some selected experiments within a “pouring” scenario. Further, although this study is oriented to mobile service robots, the modularized design of hardware and software makes its extensive use feasible in other types of service robots like smart rehabilitation beds, wheelchairs, and cleaning equipments.

This study deals with a self-reconfiguration problem of hexagonal-shaped modules from an arbitrary initial configuration to a straight chain. Modules are modeled as the same-sized rigid bodies. Two categories of modules with different functionalities are used. One category comprises two powerful modules, which are expected to play the role of terminal modules in a goal configuration. The other category comprises several ordinary modules, which are expected to fill in the middle portion in a goal configuration. A distributed control strategy, inspired by the idea of curve shortening, is developed for each module to act cooperatively to attain a goal configuration. It is verified that under the proposed strategy, modules eventually converge to a straight chain.

We present BioBug, a bionic cognitive response navigation algorithm for mobile robots based on neuroethology principles. It includes a biological antenna model for environment perception and an improved Bug algorithm for motion planning and control. The biological antenna model delineates the interested sensing areas, and thus decreases the computational burden. Then, this obtained environment stimulation is responded to generate the corresponding walking behavior according to BioBug. Simulations and experiments have been carried out in different conditions of obstacle density and boundary shape through algorithm comparisons. Compared with the competitors, BioBug is characterized by not only a smaller path length, but also shorter time for obstacle escape. The results demonstrate the practicality, environment robustness, and obstacle avoidance efficiency of the algorithm.

In this paper, we focus on the unknown environments without artificial landmarks and features, such as disaster situations and polar regions. An approach to active exploration based on an on-line scheme for autonomous allocation of landmarks is proposed. Specifically, the robot carries along with itself some landmarks which are to be allocated during the exploration according to some heuristic rules. The utility of landmark allocation is analyzed and calculated. Then the active exploration is converted into a problem of multi-objective optimization. The objective function includes three weighted terms: the accuracy of localization and mapping, the coverage rate of the unknown environment and the utility of the allocated landmarks. By solving this optimization problem, control inputs of the robot are computed to guarantee that accurate localization, high-quality mapping and complete exploration can be achieved simultaneously. Moreover, supplementation and redundancy elimination of the allocated landmarks are executed to make a complete and non-redundant coverage for the environment. Finally, some landmarks, together with a device for allocating these landmarks, are developed. Both experiment and simulation results are presented to demonstrate the effectiveness of the proposed approach.

Considering undesired slippage between manipulated object and finger tips of a multi-robot system, adaptive control synthesis of the object grasping and manipulation is addressed in this paper. Although many studies can be found in the literature dealing with grasp analysis and grasp synthesis, most assume no slippage between the finger tips and the object. Slippage can occur for many reasons such as disturbances, uncertainties in parameters, and dynamics of the system. In this paper, system dynamics is analyzed using a new presentation of friction and slippage dynamics. Then an adaptive control law is proposed for trajectory tracking and slippage control of the object as well as compensation for parameter uncertainties of the system, such as mass properties and coefficients of friction. Stability of the proposed adaptive controller is studied analytically and the performance of the system is studied numerically.

One of the main challenges in robotics is navigating autonomously through large, unknown, and unstructured environments. Simultaneous localization and mapping (SLAM) is currently regarded as a viable solution for this problem. As the traditional metric approach to SLAM is experiencing computational difficulties when exploring large areas, increasing attention is being paid to topological SLAM, which is bound to provide sufficiently accurate location estimates, while being significantly less computationally demanding. This paper intends to provide an introductory overview of the most prominent techniques that have been applied to topological SLAM in terms of feature detection, map matching, and map fusion.

This paper focuses on the mechanism design of a slide-block structure and its application on a biomimetic modular robotic fish for three-dimensional swimming. First, as a barycenter-adjustor, the slide-block structure is integrated into a mechanical design of a robotic fish, which is constructed by a control module, a driving module, and a fan-shaped caudal fin. The three-dimensional locomotion of robotic fish is decomposed into two-dimensional locomotion in horizontal plane and ascent–descent locomotion in vertical plane. Both the kinematics of the horizontal swim and the dynamics of the ascent–descent swim are analyzed by the curve fitting method. Finally, experimental results validate the three-dimensional swimming capability of the robotic fish. Furthermore, the impact of two design parameters on the swimming capability of the robotic fish is discussed by the experimental method. The experimental results confirm that the robotic fish with one driving module and a fan-shaped low-aspect-ratio caudal foil can produce higher propulsive speed than other parameter combinations.