Showing papers by "Rajnikant Sharma published in 2009"

Collision avoidance between UAV clusters using swarm intelligence techniques

Abstract: In this article, several basic swarming laws for Unmanned Aerial Vehicles (UAVs) are developed for both two-dimensional (2D) plane and three-dimensional (3D) space. Effects of these basic laws on the group behaviour of swarms of UAVs are studied. It is shown that when cohesion rule is applied an equilibrium condition is reached in which all the UAVs settle at the same altitude on a circle of constant radius. It is also proved analytically that this equilibrium condition is stable for all values of velocity and acceleration. A decentralised autonomous decision-making approach that achieves collision avoidance without any central authority is also proposed in this article. Algorithms are developed with the help of these swarming laws for two types of collision avoidance, Group-wise and Individual, in 2D plane and 3D space. Effect of various parameters are studied on both types of collision avoidance schemes through extensive simulations.

Vision Based Distributed Cooperative Navigation for MAVs in GPS denied areas

Abstract: Current Miniature Air Vehicle (MAV) systems rely on the availability of GPS to enable navigation (state estimation) during ∞ight. However, many envisioned MAV usage scenarios require MAVs that can ∞y in tightly constrained spaces (e.g., urban terrain, indoors, dense jungle, etc.) meaning that GPS may not be available. While inertial sensors can be used to estimate navigation state, their estimates will diverge over time without GPS. In this paper, we propose a method for overcoming this drift in a multiple-MAV scenario. We develop a distributed cooperative navigation system where each MAV is equipped with a bearing-only sensor (an electro-optical camera) and an inertial measurement unit. The camera is used to measure the bearing from other MAVs and/or landmarks which are in its fleld of view. By communicating local bearing information with other MAVs in their communication range, each MAV can estimate, without drift, its navigation state assuming the entire system of MAVs observes two or more landmarks at known locations. The distributed cooperative navigation system explicitly minimizes communication both in terms of message size and number of communication links. We describe su‐cient conditions for eliminating drift in the connectivity of the MAVs and how many landmarks are observed. We present simulation results to support the developed theory.

Reactive Collision Avoidance for Fixed-wing MAVs Flying in Urban Terrain

Abstract: Flying flxed-wing miniature air vehicles (FW-MAVs) in urban terrain is a challenging task because of unstructured urban environments, the minimum speed requirement for ∞ight of flxed-wing vehicles, and the non-holonomic characteristics of FW-MAVs. While traditional path-planning algorithms can efiectively overcome many of these constraints, if the FW-MAV detects new obstacles in-∞ight that were not included in the initial pathplanning, immediate action must be taken to avoid collision. Re-planning with traditional path-planning algorithms is not feasible due to the time required to plan an entire path. Therefore, a reactive collision avoidance system must be used to guarantee obstacle avoidance until a new path can be planned which includes the newly sensed information. In this paper we develop a reactive nonlinear collision avoidance guidance law for FWMAVs ∞ying in urban terrain. Our guidance law is designed for the scenario where a wall or other large object is observed. In this case, we would like the FW-MAV to maintain a specifled safe distance away from the obstacle over time. The algorithm is developed using Lyapunov stability theory, relative geometry between the FW-MAV and the obstacle. The FW-MAV reacts given the range information between the FW-MAV and the obstacle at a constant bearing. We show that our guidance law guarantees the convergence of distance between the FW-MAV and the obstacle to the desired safe distance. We also derive a sliding mode controller to take into account the uncertainty in wall orientation. Simulation results show that the guidance law is successful in navigating the FW-MAV between zigzag walls, non parallel walls, and curved walls.

Study of human exposure to fine particulates and respiratory tract depositions in residents of an industrial environment in India

Abstract: 3for various categories. Chemical analysis of PM samples shows that higher risk is associated with housewives who spend their time (> 85%) indoors. Good positive correlation coef ficient value is found for PM concentrations and respiratory tract depositions.