Mathematical modeling and vertical flight control of a tilt-wing UAV

This paper presents a mathematical model and vertical flight control algorithms for a new tilt-wing unmanned aerial vehicle (UAV). The vehicle is capable of vertical take-off and landing (VTOL). Due to its tilt-wing structure, it can also fly horizontally. The mathematical model of the vehicle is obtained using Newton-Euler formulation. A gravity compensated PID controller is designed for altitude control, and three PID controllers are designed for attitude stabilization of the vehicle. Performances of these controllers are found to be quite satisfactory as demonstrated by indoor and outdoor flight experiments

Reliable and Energy Efficient MLC STT-RAM Buffer for CNN Accelerators

We propose a lightweight scheme where the formation of a data block is changed in such a way that it can tolerate soft errors significantly better than the baseline. The key insight behind our work is that CNN weights are normalized between -1 and 1 after each convolutional layer, and this leaves one bit unused in half-precision floating-point representation. By taking advantage of the unused bit, we create a backup for the most significant bit to protect it against the soft errors. Also, considering the fact that in MLC STT-RAMs the cost of memory operations (read and write), and reliability of a cell are content-dependent (some patterns take larger current and longer time, while they are more susceptible to soft error), we rearrange the data block to minimize the number of costly bit patterns. Combining these two techniques provides the same level of accuracy compared to an error-free baseline while improving the read and write energy by 9% and 6%, respectively

Labour efficiency on-farm

End of project reportImprovements in milking efficiency have a greater influence than any other aspect of the dairy farmers work on overall farm labour inputs (Whipp, 1992). In order to facilitate the examination of milking process labour inputs, the milking process may be divided into the following three components: herding pre and post milking (transfer of cows to and from the milking parlour); milking (milking tasks / work routines within the parlour); and washing (washing of milking machine and yard). Meanwhile, within milking specifically, the number of cows milked per operator per hour is the best measure of both the performance of the operator and the milking installation (Clough, 1978). This is affected by the following three factors: the milking times of the cows, the number and arrangement of the milking units, and the operator’s work routine (Whipp, 1992). The addition of extra milking units will only increase milking performance if the operator has idle time during milking (Hansen, 1999)

Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation

We develop an approach that benefits from large simulated datasets and takes full advantage of the limited online data that is most relevant. We propose a variant of Bayesian optimization that alternates between using informed and uninformed kernels. With this Bernoulli Alternation Kernel we ensure that discrepancies between simulation and reality do not hinder adapting robot control policies online. The proposed approach is applied to a challenging real-world problem of task-oriented grasping with novel objects. Our further contribution is a neural network architecture and training pipeline that use experience from grasping objects in simulation to learn grasp stability scores. We learn task scores from a labeled dataset with a convolutional network, which is used to construct an informed kernel for our variant of Bayesian optimization. Experiments on an ABB Yumi robot with real sensor data demonstrate success of our approach, despite the challenge of fulfilling task requirements and high uncertainty over physical properties of objects.Comment: To appear in 2nd Conference on Robot Learning (CoRL) 201

Latency Optimized Asynchronous Early Output Ripple Carry Adder based on Delay-Insensitive Dual-Rail Data Encoding

Asynchronous circuits employing delay-insensitive codes for data representation i.e. encoding and following a 4-phase return-to-zero protocol for handshaking are generally robust. Depending upon whether a single delay-insensitive code or multiple delay-insensitive code(s) are used for data encoding, the encoding scheme is called homogeneous or heterogeneous delay-insensitive data encoding. This article proposes a new latency optimized early output asynchronous ripple carry adder (RCA) that utilizes single-bit asynchronous full adders (SAFAs) and dual-bit asynchronous full adders (DAFAs) which incorporate redundant logic and are based on the delay-insensitive dual-rail code i.e. homogeneous data encoding, and follow a 4-phase return-to-zero handshaking. Amongst various RCA, carry lookahead adder (CLA), and carry select adder (CSLA) designs, which are based on homogeneous or heterogeneous delay-insensitive data encodings which correspond to the weak-indication or the early output timing model, the proposed early output asynchronous RCA that incorporates SAFAs and DAFAs with redundant logic is found to result in reduced latency for a dual-operand addition operation. In particular, for a 32-bit asynchronous RCA, utilizing 15 stages of DAFAs and 2 stages of SAFAs leads to reduced latency. The theoretical worst-case latencies of the different asynchronous adders were calculated by taking into account the typical gate delays of a 32/28nm CMOS digital cell library, and a comparison is made with their practical worst-case latencies estimated. The theoretical and practical worst-case latencies show a close correlation....Comment: arXiv admin note: text overlap with arXiv:1704.0761