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Describes two types of mobile robots designed for the US military. One is the mobile detection assessment response system (MDARS), which is an automated robotic security and inventory system capable of patrolling interior and exterior warehouses and storage sites for the Department of Defense. The other is the spiral track autonomous robot (STAR), a multi‐terrain military vehicle used to reduce risk to military personnel and equipment. Both autonomous robots allow the US military to decrease unsecured threats and to increase savings which arise from the prevention of expensive hardware loss.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

This paper aims to incorporate a hybridized advanced sine-cosine algorithm (ASCA) and advanced ant colony optimization (AACO) technique for optimal path search with control over multiple mobile robots in static and dynamic unknown environments.

The controller for ASCA and AACO is designed and implemented through MATLAB simulation coupled with real-time experiments in various environments. Whenever the sensors detect obstacles, ASCA is applied to find their global best positions within the sensing range, following which AACO is activated to choose the next stand-point. This is how the robot travels to the specified target point.

Navigational analysis is carried out by implementing the technique developed here using single and multiple mobile robots. Its efficiency is authenticated through the comparison between simulation and experimental results. Further, the proposed technique is found to be more efficient when compared with existing methodologies. Significant improvements of about 10.21 per cent in path length are achieved along with better control over these.

Systematic presentation of the proposed technique attracts a wide readership among researchers where AI technique is the application criteria.

This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.

The presentation of in-vehicle warnings information at risky driving scenarios is aimed to improve the collision avoidance ability of drivers. Existing studies have found that driver’s collision avoidance performance is affected by both warning information and driver’s workload. However, whether moderation and mediation effects exist among warning information, driver’s cognition, behavior and risky avoidance performance is unclear.

This purpose of this study is to examine whether the warning information type modifies the relationship between the forward collision risk and collision avoidance behavior. A driving simulator experiment was conducted with waring and command information.

Results of 30 participants indicated that command information improves collision avoidance behavior more than notification warning under the forward collision risky driving scenario. The primary reason for this is that collision avoidance behavior can be negatively affected by the forward collision risk. At the same time, command information can weaken this negative effect. Moreover, improved collision avoidance behavior can be achieved through increasing drivers’ mental workload.

The proposed model provides a comprehensive understanding of the factors influencing collision avoidance behavior, thus contributing to improved in-vehicle information system design.

The significant moderation effects evoke the fact that information types and mental workloads are critical in improving drivers’ collision avoidance ability. Through further calibration with larger sample size, the proposed structural model can be used to predict the effect of in-vehicle warnings in different risky driving scenarios.

Unmanned aerial vehicles (UAVs) have a wide variety of applications such as surveillance and search. Many of these tasks are better executed by multiple UAVs acting as a group. One of the main problems to be tackled in a high‐density UAV traffic scenario is that of collision avoidance among UAVs. The purpose of this paper is to give a collision avoidance algorithm to detect and resolve the conflicts of projected path among UAVs.

The collision avoidance algorithm developed in the paper handles multiple UAV conflicts by considering only the most imminent predicted collision and doing a maneuver to increase the line‐of‐sight rate to avoid that conflict. After the collision avoidance maneuver, the UAVs fly to their destinations via Dubins shortest path to minimize time to reach destination. The algorithm is tested on realistic six degree of freedom UAV models augmented with proportional‐integral controllers to hold altitude, velocity, and commanded bank angles.

The paper shows, through extensive simulations, that the proposed collision avoidance algorithm gives a good performance in high‐density UAV traffic scenarios. The proposed collision avoidance algorithm is simple to implement and is computationally efficient.

The algorithm developed in this paper can be easily implemented on actual UAVs.

There are only a few works in the literature that address multiple UAV collision avoidance in very high‐density traffic situations. This paper addresses very high‐density multiple UAV conflict resolution with realistic UAV models.

The ‘Air‐O‐FIow’ industrial vacuum cleaner was introduced recently when it was demonstrated in a wide range of cleaning applications. The unit works on the Venturi principle from a compressed air line at or above the standard pressure of 80 lb./sq. in. and will ‘inhale’ a large variety of ‘foreign bodies’—including broken glass, nuts and bolts, steel swarf and liquids. The unit has three interchangeable nozzles and a mobile stand, overall height is 23½ in. with a diameter of 11 in. and weighs 14½ lb. empty. The National Gas Turbines Establishment employs the ‘Air‐O‐Flow’ unit for the transfer of engineering machine suds and Handley Page, who were supplied with the equipment by the Royal Air Force, use it for extracting fuel from the tanks of the Victor.