Autonomous navigation has been a long-standing research topic, and researchers have worked on many challenging problems in indoor and outdoor environments. One application area of navigation solutions is material handling in industrial environments. With Industry 4.0, the simple problem in traditional factories has evolved into the use of autonomous mobile robots within flexible production islands in a self-decision-making structure. Two main stages of such a navigation system are safe transportation of the vehicle from one point to another and reaching destinations at industrial standards. The main concern in the former is roughly determining the vehicle’s pose to follow the route, while the latter aims to reach the target with high accuracy and precision. Often, it may not be possible or require extra effort to satisfy requirements with a single localization method. Therefore, a multi-stage localization approach is proposed in this study. Particle filter-based large-scale localization approaches are utilized during the vehicle’s movement from one point to another, while scan-matching-based methods are used in the docking stage. The localization system enables the appropriate approach based on the vehicle’s status and task through a decision-making mechanism. The decision-making mechanism uses a similarity metric obtained through the correntropy criterion to decide when and how to switch from large-scale localization to precise localization. The feasibility and performance of the developed method are corroborated through field tests. These evaluations demonstrate that the proposed method accomplishes tasks with sub-centimeter and sub-degree accuracy and precision without affecting the operation of the navigation algorithms in real time.

Today, robots can be found helping humans with their daily tasks. Some tasks require the robot to visit a set of locations in the environment efficiently, like in the Traveling Salesman Problem. As indoor environments are maze-like areas, feasible paths connecting locations must be computed beforehand, so they can be combined during the scheduling, which can be impracticable for real-time applications. This work presents an on-line Route Scheduling supported by a Fast Path Planning Method able to adjust pre-built paths. Experiments were carried out with virtual and real robots to evaluate time and quality of tours.

While initially conceived for human motion augmentation, wearable robots have gradually evolved as technological aids in motion assistance and rehabilitation. There are increasing real-world applications in industrial and medical scenarios. Though efforts have been made on wearable robotic systems, e.g. robotic prostheses and exoskeletons, there are still several challenges in kinematics and actuation solutions, dynamic analysis and control of human-robot systems, neuro-control and human-robot interfaces; ergonomics and human-in-the-loop optimization. Meanwhile, real-world applications in industrial or medical scenarios are facing difficulties considering effectiveness.

It has become a common practice to use simulation to generate large databases of good grasps for grasp planning in robotics research. However, the existence of a generic simulation context that enables the generation of high quality grasps that can be used in several different contexts such as bin-picking or picking objects from a table, has to our knowledge not yet been discussed in the literature.

In this paper, we investigate how well the quality of grasps simulated in a commonly used “generic” context transfers to a specific context, both, in simulation and in the real world.

We generate a large database of grasp hypotheses for several objects and grippers, which we then evaluate in different dynamic simulation contexts e.g., free floating (no gravity, no obstacles), standing on a table and lying on a table.

We present a comparison on the intersection of the grasp outcome space across the different contexts and quantitatively show that to generate reliable grasp databases, it is important to use context specific simulation.

We furthermore evaluate how well a state of the art grasp database transfers from two simulated contexts to a real world context of picking an object from a table and discuss how to evaluate transferability into non-deterministic real world contexts.

This paper presents a study of the application of adaptive and robust control methods to a cooperative manipulation system which is developed for handling an object by three dimensional revolute-jointed manipulators. The adaptive control algorithm supports the parameter adaptive law that provides guaranteed stability for uncertain systems. In designing the robust control structure, contact and friction constraints for grasp and bearing conditions, structural flexibility or such similar factors as various unmodeled dynamics are considered as uncertainties that determine available values of control parameters. The novelty of results in the present paper is to define new control inputs using parametric uncertainties and the Lyapunov based theory of guaranteed stability of uncertain systems for handling objects in a spatial workspace.

A negative pressure wall-climbing robot is a special robot for climbing vertical walls, which is widely used in construction, petrochemicals, nuclear energy, shipbuilding, and other industries. The mobility and adhesion of the wheel-track wall-climbing robot with steering-straight mode are significantly decreased on the cylindrical wall, especially during steering. The reason is that the suction chamber may separate from the wall and the required driving force for movement increases, during steering. In this paper, a negative pressure wall-climbing robot with omnidirectional movement mode is developed. By introducing a compliant adjusting suction mechanism and omni-belt wheels, an omnidirectional movement mode is formed instead of the steering-straight mode, and the performances of adhesion and mobility are improved. We establish the safety adhesion model for the robot on a cylindrical wall and obtain the safety adhesion forces. We designed and manufactured an experimental prototype based on the analysis. Experiments showed that the robot has the ability of full maneuverability in cylindrical walls.

Motion planning for high-DOF multi-arm systems operating in complex environments remains a challenging problem, with many motion planning algorithms requiring evaluation of the minimum collision distance and its derivative. Because of the computational complexity of calculating the collision distance, recent methods have attempted to leverage data-driven machine learning methods to learn the collision distance. Because of the significant training dataset requirements for high-DOF robots, existing kernel-based methods, which require $O(N^2)$ memory and computation resources, where $N$ denotes the number of dataset points, often perform poorly. This paper proposes a new active learning method for learning the collision distance function that overcomes the limitations of existing methods: (i) the size of the training dataset remains fixed, with the dataset containing more points near the collision boundary as learning proceeds, and (ii) calculating collision distances in the higher-dimensional link $SE(3)^n$ configuration space – here $n$ denotes the number of links – leads to more accurate and robust collision distance function learning. Performance evaluations with high-DOF multi-arm robot systems demonstrate the advantages of the proposed active learning-based strategy vis-$\grave{\text{a}}$-vis existing learning-based methods.

Navigating along a set of programmed points in a completely unknown environment is a challenging task which mostly depends on the way the robot perceives and symbolizes the environment and decisions it takes in order to avoid the obstacles while it intends to reach subsequent goals. Tenacity and Traversability (T2)1-based strategies have demonstrated to be highly effective for reactive navigation, extending the benefits of the artificial Potential Field method to complex situations, such as trapping zones or mazes. This paper presents a new approach for reactive mobile robot behavior control which rules the actions to be performed to avoid unexpected obstacles while the robot executes a mission between several defined sites. This new strategy combines the T2 principles to escape from trapping zones together with additional criteria based on the Nearness Diagram (ND)13 strategy to move in cluttered or densely occupied scenarios. Success in a complete set of experiments, using a mobile robot equipped with a single camera, shows extensive environmental conditions where the strategy can be applied.

This article proposes an observer design for two important variables in the studies of single-leg hopping robot (SLHR), the apex height, and the vertical velocity of SLHR during its stance phase. At first, the Euler–Lagrange (EL) dynamics of SLHR are obtained and apex height is identified in the state-space representation of the EL dynamics. Apex height is the state variable that represents the robot body’s height at the top point, which keeps on changing as the robot functions. Vertical velocity is the velocity of the robot in the vertical direction. An observer design is presented in this article which will estimate these variables when required. The quality of the estimation is validated by the simulation results where the estimation error is zero which means the model output is correct and observer performance is good.

Engineers have traditionally invested in Advanced Manufacturing Technology (AMT), such as FMS, Robots, CAD/CAM, CNC and MRP to achieve a reduction in the labour force. Similarly, government incentives for introducing AMT, have also placed an undue emphasis on the ‘need to replace labour with technology’. This policy creates severe industrial relations problems and leads to the view that technology, especially robots, ‘competes’ with human beings for employment. Research at U.M.I.S.T. has shown that AMT is much more viable when the objective of the investment is to increase a company's overall competitive ability, thereby generating increased sales which, in turn, necessitates an INCREASED labour force. The paper discusses various aspects of AMT and in each case it is shown how the acceptability of the investment is improved when the new technology is viewed ‘company-wide’. When this occurs, technology is viewed as being ‘complementary to’ and not ‘instead of’ humans.

The early applications of Visual Simultaneous Localization and Mapping (VSLAM) technology were primarily focused on static environments, relying on the static nature of the environment for map construction and localization. However, in practical applications, we often encounter various dynamic environments, such as city streets, where moving objects are present. These dynamic objects can make it challenging for robots to accurately understand their own position. This paper proposes a real-time localization and mapping method tailored for dynamic environments to effectively deal with the interference of moving objects in such settings. Firstly, depth images are clustered, and they are subdivided into sub-point clouds to obtain clearer local information. Secondly, when processing regular frames, we fully exploit the structural invariance of static sub-point clouds and their relative relationships. Among these, the concept of the sub-point cloud is introduced as novel idea in this paper. By utilizing the results computed based on sub-poses, we can effectively quantify the disparities between regular frames and reference frames. This enables us to accurately detect dynamic areas within the regular frames. Furthermore, by refining the dynamic areas of keyframes using historical observation data, the robustness of the system is further enhanced. We conducted comprehensive experimental evaluations on challenging dynamic sequences from the TUM dataset and compared our approach with state-of-the-art dynamic VSLAM systems. The experimental results demonstrate that our method significantly enhances the accuracy and robustness of pose estimation. Additionally, we validated the effectiveness of the system in dynamic environments through real-world scenario tests.

The objective of this work is to construct a robot that is based on 3D printing to meet the low-cost and light structures. The Computer-aided-design model is used with LabVIEW to simulate the given trajectory. Users of the simulation of such methodology can preview the simulated motion and perceive and resolve discrepancies between the planned and simulated paths prior to execution of a task. The advantages of this study are the lack of need to mount extra sensors on realistic robot to measure joint space coordinates, simplifying the hardware. These outcomes can also be used in an undergraduate robotics course.

This paper presents a concept of sequentially actuated multi-degree-of-freedom (DOF) robot with only one motor. A switching mechanism allowing to actuate sequentially the different joints–or combinations of the joints–of the robot is also proposed. Potential actuation schemes (joint combinations) are presented and their properties are discussed. Cartesian pick-and-place trajectories are then considered using different actuation schemes. An optimisation algorithm is presented in order to provide the best possible sequence by minimising the amplitude of the joint rotations for a given actuation combination. A simple planar two-DOF and the SCARA architectures are used to illustrate the concept. Finally, a prototype is developed with the aim of demonstrating the sequentially actuated manipulator concept.

As a heavy load is applied to the parallel manipulators, it causes inaccuracies while positioning the end-effector or unbalanced dynamic forces in the legs. Various load-balancing techniques overcome this. However, the disadvantage of most load-balancing mechanisms is that they add inertia to the assembly and decrease the speed of motion. This article studies a new load-balancing method (a passive damper mechanism). The passive balancing mechanism is proposed to negate the inertia effects while countering the static inaccuracies in the parallel mechanism. This is verified by the structural analysis of the mechanism. The impact of the damper element on the dynamics of the mechanism is unknown. Hence, a complete mathematical model for the balancing mechanism has been developed to study its impact on the dynamics of the entire structure. Laplace transformations characterize the system response. The inclusion of a passive damper in a 3-prismatic-prismatic-revolute-spherical system was examined and found to be stable and critically damped. Such a passive damper was envisaged to facilitate additional force transmission for the actuators, and the DC gain from the system response validates the torque support for the actuators.

This paper describes the development of a desktop robotic system that enables the plug-and-play function through the USB (universal serial bus) port of a personal computer (PC). Thus a new kind of desktop PC peripheral is invented that has programmable manipulability. The robotic system is realized on an internally distributed control structure that facilitates higher system reliability. A PID control algorithm is implemented on a prototype of the proposed system, to demonstrate the system's ability to implement feedback control. Experimental results show the performance and properties of the proposed system.