Advances in Robotics & Automation

The report represents the peculiarities of using intelligent airbags in cars. A review is made of the sensors used to activate the airbag system in terms of their advantages and disadvantages. Presented are software applications using the capabilities of the hardware of sensor devices in order to build a common signal. Based on a study of literature is developed a software sensor for airbag deployment depending on the object on passenger seat. The work of this sensor is studied in case of interrupted any of the input signals. The results show that by combining data from three hardware sensors is received error up to 5% in distinguish between the objects on the passenger seat of the car. The dropping of the signal in hardware sensors affects the accuracy of i dentifying the object on the passenger seat.

Industrial robots have been widely used in various fields. The joint angle error is the main factor that affects the accuracy performance of the robot. It is important to notice that these kinematic parameters error cannot be eliminated from the robot system completely. Even after calibration, these errors still exist and will be fluctuated during the robot system running. This paper proposed a new method of finding the best position and orientation to perform a specific working path based on the current accuracy capacity of the robot system. By analyzing the robot forward/inverse kinematic and the angle error sensitivity of different joint in the serial manipulator system, a new evaluation formulation is established for mapping the trajectory accuracy within the robot’s working volume. The influence of different position and orientation on the movement accuracy of the end effector has been verified by experiments and discussed thoroughly. Finally, a visualized evaluation map can be obtained to describe the accuracy difference of a robotic laser deposition working path at different positions and orientations. This method is helpful for making the maximum usage of the robot’s current accuracy ability rather than blindly pursuing the higher accuracy of the robot system.

Autonomous indoor navigation is synonymous with military centric autonomous navigation in GPS-denied environments. Unmanned aerial systems (UAS) are routinely connected to autonomous navigation. This combination of technology has many disparate uses such as in kids toys, photography, and military applications. For each of these areas a major concern is size, weight, and power (SWaP) in the product design. SWaP has a direct effect on the operations of an autonomous UAS such as on the flight time, the maneuverability, controllability, and the durability. This paper presents a basic algorithm describing one aspect of reducing SWaP on an autonomous quad-rotor UAS, by converting a 2D scanning LiDAR sensor to a 3D sensor, thus eliminating the need for additional sensors used to perform localization and mapping. Much that is described here is derived from the thesis work presented by Cooper. The majority of work was performed during a Master’s Thesis investigation by M. A. Cooper titled “Converting a 2D Scanning LiDAR to a 3D System for Use on Quad-Rotor UAVs in Autonomous Navigation.” The work presented here develops the generalized calibration procedure.

In this paper, we presented a light, reliable underwater robot made of Poly Tetra Fluoro Ethylene (PTFE) which has a high safety coefficient against the forces being applied on it in different circumstances of the sea depths in addition to being light, cheap and also we presented a very quick and low-cost method for sealing off this robot made of Teflon.