Automatic Path Planning and Control Design for Autonomous Landing of UAVs using Dynamic Inversion

In this paper a nonlinear control has been designed using the dynamic inversion approach for automatic landing of unmanned aerial vehicles (UAVs), along with associated path planning. This is a difficult problem because of light weight of UAVs and strong coupling between longitudinal and lateral modes. The landing maneuver of the UAV is divided into approach, glideslope and flare. In the approach UAV aligns with the centerline of the runway by heading angle correction. In glideslope and flare the UAV follows straight line and exponential curves respectively in the pitch plane with no lateral deviations. The glideslope and flare path are scheduled as a function of approach distance from runway. The trajectory parameters are calculated such that the sink rate at touchdown remains within specified bounds. It is also ensured that the transition from the glideslope to flare path is smooth by ensuring C-1 continuity at the transition. In the outer loop, the roll rate command is generated by assuring a coordinated turn in the alignment segment and by assuring zero bank angle in the glideslope and flare segments. The pitch rate command is generated from the error in altitude to control the deviations from the landing trajectory. The yaw rate command is generated from the required heading correction. In the inner loop, the aileron, elevator and rudder deflections are computed together to track the required body rate commands. Moreover, it is also ensured that the forward velocity of the UAV at the touch down remains close to a desired value by manipulating the thrust of the vehicle. A nonlinear six-DOF model, which has been developed from extensive wind-tunnel testing, is used both for control design as well as to validate it.

Wind loading over the top portions of tall stacks with and without external landing platforms

The variation of the drag force near the top portions of tall stacks with and without external landing platforms, and with the exit open and closed, has been examined by model studies in a wind tunnel at Reynolds numbers of about 10(5). Pressure measurements on three models of different height to diameter ratios have been supplemented by flow visualisation studies. Observations confirm that when there is no platform, significant load enhancement over the top three to four diameters occurs, due to the high suction caused by the sharp separation of the flow over the top from the rim, in the aft regions of the stack. The enhanced loading is found to be greater if the exit is closed. A platform at the top, of less than twice the exit diameter, further increases the drag force near the top, but a still larger platform at the top, of about three times the exit diameter, decreases the drag force to values less than those much further below, effectively nullifying the enhanced drag force. It was found that such a reduction of the enhanced drag force in the top regions can also be achieved by a smaller platform of 1.1 to 1.3 times the local diameter, located at about three to five diameters below the top.

Inverse Polynomial Based Explicit Guidance for Lunar Soft Landing During Powered Braking

In this paper an explicit guidance law for the powered descent phase of the soft lunar landing is presented. The descent trajectory, expressed in polynomial form is fixed based on the boundary conditions imposed by the precise soft landing mission. Adapting an inverse model based approach, the guidance command is computed from the known spacecraft trajectory. The guidance formulation ensures the vertical orientation of the spacecraft during touchdown. Also a closed form relation for the final flight time is proposed. The final time is expressed as a function of initial position and velocity of the spacecraft ( at the start of descent) and also depends on the desired landing site. To ensure the fuel minimum descent the proposed explicit method is extended to optimal guidance formulation. The effectiveness of the proposed guidance laws are demonstrated with simulation results.

Fuel-optimal G-MPSP Guidance for Powered Descent Phase of Soft Lunar Landing

A fuel optimal nonlinear sub-optimal guidance scheme is presented in this paper for soft landing of a lunar craft during the powered descent phase. The recently developed Generalized Model Predictive Static Programming (G-MPSP) is used to compute the required magnitude and angle of the thrust vector. Both terminal position and velocity vector are imposed as hard constraints, which ensures high position accuracy and facilitates initiation of vertical descent at the end of the powered descent phase. A key feature of the G-MPSP algorithm is that it converts the nonlinear dynamic programming problem into a low-dimensional static optimization problem (of the same dimension as the output vector). The control history update is done in closed form after computing a time-varying weighting matrix through a backward integration process. This feature makes the algorithm computationally efficient, which makes it suitable for on-board applications. The effectiveness of the proposed guidance algorithm is demonstrated through promising simulation results.

Optimal Guidance for Accurate Lunar Soft Landing with Minimum Fuel Consumption using Model Predictive Static Programming

In this paper the soft lunar landing with minimum fuel expenditure is formulated as a nonlinear optimal guidance problem. The realization of pinpoint soft landing with terminal velocity and position constraints is achieved using Model Predictive Static Programming (MPSP). The high accuracy of the terminal conditions is ensured as the formulation of the MPSP inherently poses final conditions as a set of hard constraints. The computational efficiency and fast convergence make the MPSP preferable for fixed final time onboard optimal guidance algorithm. It has also been observed that the minimum fuel requirement strongly depends on the choice of the final time (a critical point that is not given due importance in many literature). Hence, to optimally select the final time, a neural network is used to learn the mapping between various initial conditions in the domain of interest and the corresponding optimal flight time. To generate the training data set, the optimal final time is computed offline using a gradient based optimization technique. The effectiveness of the proposed method is demonstrated with rigorous simulation results.

Resolution and sensitivity of the eyes of the Asian honeybees Apis florea, Apis cerana and Apis dorsata

Bees of the genus Apis are important foragers of nectar and pollen resources. Although the European honeybee, Apis mellifera, has been well studied with respect to its sensory abilities, learning behaviour and role as pollinators, much less is known about the other Apis species. We studied the anatomical spatial resolution and absolute sensitivity of the eyes of three sympatric species of Asian honeybees, Apis cerana, Apis florea and Apis dorsata and compared them with the eyes of A. mellifera. Of these four species, the giant honeybee A. dorsata (which forages during moonlit nights) has the lowest spatial resolution and the most sensitive eyes, followed by A. mellifera, A. cerana and the dwarf honeybee, A. florea (which has the smallest acceptance angles and the least sensitive eyes). Moreover, unlike the strictly diurnal A. cerana and A. florea, A. dorsata possess large ocelli, a feature that it shares with all dim-light bees. However, the eyes of the facultatively nocturnal A. dorsata are much less sensitive than those of known obligately nocturnal bees such as Megalopta genalis in Panama and Xylocopa tranquebarica in India. The differences in sensitivity between the eyes of A. dorsata and other strictly diurnal Apis species cannot alone explain why the former is able to fly, orient and forage at half-moon light levels. We assume that additional neuronal adaptations, as has been proposed for A. mellifera, M. genalis and X. tranquebarica, might exist in A. dorsata.

Bat foraging strategies and pollination of Madhuca latifolia (Sapotaceae) in southern India

The sympatrically occurring Indian short-nosed fruit bat Cynopterus sphinx and Indian flying fox Pteropus giganteus visit Madhuca latifolia (Sapotaceae), which offers fleshy corollas (approximate to 300 mg) to pollinating bats. The flowers are white, tiny and in dense fascicles The foraging activities of the two bat species were segregated in space and time. Cynopterus sphinx fed on resources at lower heights in the trees than P giganteus and its peak foraging activity occurred at 19 30 h, before that of P giganteus Foraging activities involved short searching flights followed by landing and removal of the corolla by mouth Cynopterus sphinx detached single corollas from fascicles and carried them to nearby feeding roosts, where it sucked the juice and spat out the Fibrous remains Pteropus giganteus landed on top of the trees and fed on the corollas in situ, its peak activity occurred at 20 30 11 This species glided and crawled between the branches and held the branches with claws and forearms when removing fleshy corollas with Its Mouth Both C sphinx and P giganteus consumed fleshy corollas with attached stamens and left the gynoecium intact Bagging experiments showed that fruit-set in bat-visited flowers was significantly higher (P < 0.001) than in self-pollinated flowers.

Evaluating ILS and MLS Sites without Flight Tests

Instrument landing systems (ILS) and the upcoming microwave landing systems (MLS) are (or are planned to be) very important navigational aids at most major airports of the world. However, their performance is directly affected by the features of the site in which they are located. Currently, validation of the ILS performance is through costly and time-consuming experimental methods. This paper outlines a powerful and versatile analytical approach for performing the site evaluation, as an alternative to the experimental methods. The approach combines a multi-plate model for the terrain with a powerful and exhaustive ray-tracing technique and a versatile and accurate formulation for estimating the electromagnetic fields due to the array antenna in the presence of the terrain. It can model the effects of the undulation, the roughness and the impedance (depending on the soil type) of the terrain at the site. The results computed from the analytical method are compared with the actual measurements and good agreement is shown. Considerations for site effects on MLS are also outlined.

ILS glideslope evaluation for imperfect terrain

Instrument landing systems (ILS) are normally designed assuming the site around them to be flat. Uneven terrain results in undulations in the glidescope. In recent years, models have been evolved for predicting such aberrations as a simpler alternative to experimental methods. Such modeling normally assumes the ground to be fully conducting. A method is presented for considering imperfect terrain conductivity within the framework of the uniform theory of diffraction (UTD). A single impedance wedge formulation is developed to a form that resembles the standard form of UTD, with only one extra term in the diffraction coefficient. This extends the applicability of the standard UTD formulation and software packages to the case of the imperfectly conducting terrain. The method has been applied to a real airport site in India and improved agreement with measured glidescope parameters is demonstrated

An investigation of well-characterized small gold clusters by photoelectron spectroscopy, tunneling spectroscopy, and cognate techniques

After microscopic characterization of the size distributions of gold clusters, deposited on carbon substrates by vacuum evaporation or by soft landing, Au(4f') binding energy of the clusters has been measured as a function of the mean cluster size. Similar measurements have been carried out on Au clusters prepared from sols by chemical means and high-nuclearity cluster compounds. In general, small clusters with a mean diameter of $2 nm show significantly larger binding energies than the bulk metal value, due to the onset of nonmetallicity. Nonmetallicity manifests itself in terms of a tunneling conductance gap only in clusters of diameter ;5 1 nm containing 40 atoms or fewer.

An Efficient Simulated Annealing With a Valid Solution Mechanism For TDMA Brodcast Scheduling problem

This paper presents an efficient Simulated Annealing with valid solution mechanism for finding an optimum conflict-free transmission schedule for a broadcast radio network. This is known as a Broadcast Scheduling Problem (BSP) and shown as an NP-complete problem, in earlier studies. Because of this NP-complete nature, earlier studies used genetic algorithms, mean field annealing, neural networks, factor graph and sum product algorithm, and sequential vertex coloring algorithm to obtain the solution. In our study, a valid solution mechanism is included in simulated annealing. Because of this inclusion, we are able to achieve better results even for networks with 100 nodes and 300 links. The results obtained using our methodology is compared with all the other earlier solution methods.

Location Area Planning Using Simulated Annealing With A New Solution Representation

Location area planning problem is to partition the cellular/mobile network into location areas with the objective of minimizing the total cost. This partitioning problem is a difficult combinatorial optimization problem. In this paper, we use the simulated annealing with a new solution representation. In our method, we can automatically generate different number of location areas using Compact Index (CI) to obtain the optimal/best partitions. We compare the results obtained in our method with the earlier results available in literature. We show that our methodology is able to perform better than earlier methods.