Electric propulsion

Electric propulsion (EP) is an attractive option for unmanned orbital transfer vehicles (OTV's). Vehicles with solar electric propulsion (SEP) could be used routinely to transport cargo between nodes in Earth, lunar, and Mars orbit. Electric propulsion systems are low-thrust, high-specific-impulse systems with fuel efficiencies 2 to 10 times the efficiencies of systems using chemical propellants. The payoff for this performance can be high, since a principal cost for a space transportation system is that of launching to low Earth orbit (LEO) the propellant required for operations between LEO and other nodes. Several aspects of electric propulsion, including candidate systems and the impact of using nonterrestrial materials, are discussed

Belief Tree Search for Active Object Recognition

Active Object Recognition (AOR) has been approached as an unsupervised learning problem, in which optimal trajectories for object inspection are not known and are to be discovered by reducing label uncertainty measures or training with reinforcement learning. Such approaches have no guarantees of the quality of their solution. In this paper, we treat AOR as a Partially Observable Markov Decision Process (POMDP) and find near-optimal policies on training data using Belief Tree Search (BTS) on the corresponding belief Markov Decision Process (MDP). AOR then reduces to the problem of knowledge transfer from near-optimal policies on training set to the test set. We train a Long Short Term Memory (LSTM) network to predict the best next action on the training set rollouts. We sho that the proposed AOR method generalizes well to novel views of familiar objects and also to novel objects. We compare this supervised scheme against guided policy search, and find that the LSTM network reaches higher recognition accuracy compared to the guided policy method. We further look into optimizing the observation function to increase the total collected reward of optimal policy. In AOR, the observation function is known only approximately. We propose a gradient-based method update to this approximate observation function to increase the total reward of any policy. We show that by optimizing the observation function and retraining the supervised LSTM network, the AOR performance on the test set improves significantly.Comment: IROS 201

Telecommunications system design for the Mariner Mars 1971 spacecraft

The configuration of the Mariner Mars 1971 spacecraft telecommunications system is detailed, with particular attention to modifications performed to accommodate the orbital mission. The analysis and planning for launching are also discussed

An evaluation of oxygen-hydrogen propulsion systems for the Space Station

Conceptual designs for O2/H2 chemical and resistojet propulsion systems for the space station was developed and evaluated. The evolution of propulsion requirements was considered as the space station configuration and its utilization as a space transportation node change over the first decade of operation. The characteristics of candidate O2/H2 auxiliary propulsion systems are determined, and opportunities for integration with the OTV tank farm and the space station life support, power and thermal control subsystems are investigated. OTV tank farm boiloff can provide a major portion of the growth station impulse requirements and CO2 from the life support system can be a significant propellant resource, provided it is not denied by closure of that subsystem. Waste heat from the thermal control system is sufficient for many propellant conditioning requirements. It is concluded that the optimum level of subsystem integration must be based on higher level space station studies

Euclidean Coordinates are the Wrong Prior for Models of Primate Vision

Convolutional Neural Networks (CNNs) are currently the best models we have of the ventral temporal lobe – the part of cortex engaged in recognizing objects. They have been effective at predicting the firing rates of neurons in monkey cortex, as well as fMRI and MEG responses in human subjects. They are based on several observations concerning the visual world: 1) pixels are most correlated with nearby pixels, leading to local receptive fields; 2) stationary statistics – the statistics of image pixels are relatively invariant across the visual field, leading to replicated features 3) objects do not change identity depending on their location in the image, leading to pooling of responses, making CNNs relatively translation invariant; and 4) objects are made of parts, leading to increasing receptive field sizes in deeper layers, so smaller parts are recognized in shallower layers, and larger composites in later layers. However, compared to the primate visual system, there are a couple of striking differences. CNNs have high resolution everywhere, whereas primates have a foveated retina, with high resolution for humans only about the size of your thumbnail at arm’s length, and steep dropoff in resolution towards the periphery. The mapping from the visual field to V1 is a log-polar transform. This has two main advantages: scale is just a left-right translation, and rotation in the image plane is a vertical translation. When these are given as input to a standard CNN, scale and rotation invariance is obtained. However, translation invariance is lost, which we make up for by moving our eyes about 3 times a second. We present results from a model with these constraints, and show that, despite rotation invariance, the model is able to capture the inverted face effect, while standard CNNs do not

On the physical association of the peculiar emission: Line stars HD 122669 and HD 122691

Spectroscopic and photometric observations indicate a physical association between the peculiar early-type emission-line stars HD 122669 and HD 122691. The latter has undergone a drastic change in the strength of its emission lines during the past twenty years. There is some indication that both stars vary with shorter time scales