Traded and combined cooperative control of a smart wheelchair

This article deals with a human–machine cooperative system for the control of a smart wheelchair for people with motor disabilities. The choice of a traded control mode is first argued. The paper then pursues two objectives. The first is to describe the design of the cooperative system by focusing on the dialogue and the interaction between the pilot and the robot. The second objective is to introduce a new cooperative mode. In this one, three features are proposed: two semi-autonomous features, a wall following and a doorway crossing, during which the user can intervene punctually to rectify a trajectory or a path, and an assisted mode where, conversely, the machine intervenes in a manual control to avoid obstacles. This mode of intervention of an entity, human or machine, supervising a movement controlled by the other is referred as “combined control.” Examples of scenarios exploiting the cooperative capabilities of the system are presented and discussed.

Enhancing Robots Navigation in Internet of Things Indoor Systems

In this study, an effective local minima detection and definition algorithm is introduced for a mobile robot navigating through unknown static environments. Furthermore, five approaches are presented and compared with the popular approach wall-following to pull the robot out of the local minima enclosure namely; Random Virtual Target, Reflected Virtual Target, Global Path Backtracking, Half Path Backtracking, and Local Path Backtracking. The proposed approaches mainly depend on changing the target location temporarily to avoid the original target’s attraction force effect on the robot. Moreover, to avoid getting trapped in the same location, a virtual obstacle is placed to cover the local minima enclosure. To include the most common shapes of deadlock situations, the proposed approaches were evaluated in four different environments; V-shaped, double U-shaped, C-shaped, and cluttered environments. The results reveal that the robot, using any of the proposed approaches, requires fewer steps to reach the destination, ranging from 59 to 73 m on average, as opposed to the wall-following strategy, which requires an average of 732 m. On average, the robot with a constant speed and reflected virtual target approach takes 103 s, whereas the identical robot with a wall-following approach takes 907 s to complete the tasks. Using a fuzzy-speed robot, the duration for the wall-following approach is greatly reduced to 507 s, while the reflected virtual target may only need up to 20% of that time. More results and detailed comparisons are embedded in the subsequent sections.

Influence of Shear Wall on Seismic Response of a Structure

Structural analysis is the science of determining the effects of different loads on structures. Structural stability and stiffness are a main concern in any high-rise structures. Shear walls are structural members that are mainly responsible for resisting lateral loads predominant on structures. They are mainly responsible to increase the stiffness, reduce story drift and displacement. In order to have a comprehensive understanding about the contribution of shear wall, following research is carried out. This research involves comparing two G+16 structures; one without a shear wall and one with it. The structure has 4 bays of 3m each along X direction and Z direction. In this, we will see how shear wall resists lateral sway and reduces story drift and increases stiffness. As the height increases, the shear wall absorbs more lateral load than the frame. The software to be used for analysis is STAADPro. Keywords: STAADPro, Stiffness, storey displacement, storey drift.

Design of a Reconfigurable Wall Disinfection Robot

During a viral outbreak, such as COVID-19, autonomously operated robots are in high demand. Robots effectively improve the environmental concerns of contaminated surfaces in public spaces, such as airports, public transport areas and hospitals, that are considered high-risk areas. Indoor spaces walls made up most of the indoor areas in these public spaces and can be easily contaminated. Wall cleaning and disinfection processes are therefore critical for managing and mitigating the spread of viruses. Consequently, wall cleaning robots are preferred to address the demands. A wall cleaning robot needs to maintain a close and consistent distance away from a given wall during cleaning and disinfection processes. In this paper, a reconfigurable wall cleaning robot with autonomous wall following ability is proposed. The robot platform, Wasp, possess inter-reconfigurability, which enables it to be physically reconfigured into a wall-cleaning robot. The wall following ability has been implemented using a Fuzzy Logic System (FLS). The design of the robot and the FLS are presented in the paper. The platform and the FLS are tested and validated in several test cases. The experimental outcomes validate the real-world applicability of the proposed wall following method for a wall cleaning robot.

Early social context does not influence behavioral variation at adulthood in ants

Early experience can prepare offspring to adapt their behaviors to the environment they are likely to encounter later in life. In several species of ants, colonies show ontogenic changes in the brood-to-worker ratio that are known to have an impact on worker morphology. However, little information is available on the influence of fluctuations in the early social context on the expression of behavior in adulthood. Using the ant Lasius niger, we tested whether the brood-to-worker ratio during larval stages influenced the level of behavioral variability at adult stages. We raised batches of 20 or 180 larvae in the presence of 60 workers until adulthood. We then quantified the activity level and wall-following tendency of callow workers on ten successive trials to test the prediction that larvae reared under a high brood-to-worker ratio should show greater behavioral variations. We found that manipulation of the brood-to-worker ratio influenced the duration of development and the size of individuals at emergence. We detected no influence of early social context on the level of between- or within individual variation measured for individual activity level or on wall-following behavior. Our study suggests that behavioral traits may be more canalized than morphological traits.

Captivity-induced behaviour and spatial learning abilities in an enigmatic, aquifer-dwelling blind eel, Rakthamichthys digressus

We investigated the impact of captive life on behaviour and learning abilities in an enigmatic, aquifer-dwelling blind eel, Rakthamichthys digressus. Of eight major behavioural traits related to exploration and activity in a novel arena, four were significantly altered by life in captivity. While the startle response upon introduction into the arena and overall swimming away from the walls increased after captivity, inactivity exhibited immediately after the startle and the reaction to an external disturbance decreased. We also observed behavioural syndromes between startle responses and horizontal wall following, and between overall activity and vertical wall following; however, these behavioural syndromes were not altered by maintenance in captivity. Interestingly, this blind-eel failed to learn a simple spatial task in a Y-maze apparatus. Captive-associated behavioural changes in R. digressus may influence their survival after reintroduction into natural habitats, and such changes must be taken into account while developing protocols for ex-situ conservation and subsequent release.

Lidar-based surface following control for unmanned aerial vehicles

A simulation study is performed on a quadcopter which uses a LIDAR sensor to allow a quadcopter to navigate along and maintain a set distance from an unknown vertical surface. The dynamic equations of a quadcopter are linearized about the hovering equilibrium. For the purpose of design, all surfaces are assumed to be flat and any variations in shape are considered to be disturbances. The design process begins with the development of a potential field control design to allow the quadcopter to autonomously follow a flat surface, while maintaining a desired distance from the surface. To allow the quadcopter to follow a curved surface, the potential field technique is modified to maintain the xb axis parallel to the surface. Finally a wall following technique that directly uses the minimum range measurement to maintain the distance from the surface is developed. To simulate the control designs, a non-linear quadcopter model is used along with a model of a 2D scanning LIDAR sensor. The potential field control technique tracks flat surfaces with no steadystate error, though when curved surface following is added, a tracking error problem occurs due to measurement noise. The wall following design proves to be the superior surface following technique with greater robustness to steady-state error and results in relatively small tracking errors when navigating sinusoidal surfaces and corners.

Lidar-based surface following control for unmanned aerial vehicles

A simulation study is performed on a quadcopter which uses a LIDAR sensor to allow a quadcopter to navigate along and maintain a set distance from an unknown vertical surface. The dynamic equations of a quadcopter are linearized about the hovering equilibrium. For the purpose of design, all surfaces are assumed to be flat and any variations in shape are considered to be disturbances. The design process begins with the development of a potential field control design to allow the quadcopter to autonomously follow a flat surface, while maintaining a desired distance from the surface. To allow the quadcopter to follow a curved surface, the potential field technique is modified to maintain the xb axis parallel to the surface. Finally a wall following technique that directly uses the minimum range measurement to maintain the distance from the surface is developed. To simulate the control designs, a non-linear quadcopter model is used along with a model of a 2D scanning LIDAR sensor. The potential field control technique tracks flat surfaces with no steadystate error, though when curved surface following is added, a tracking error problem occurs due to measurement noise. The wall following design proves to be the superior surface following technique with greater robustness to steady-state error and results in relatively small tracking errors when navigating sinusoidal surfaces and corners.