15 accepted papers
In this letter, we present a comprehensive UAV system design to perform the highly complex task of off-centered aerial grasping. This task has several interdisciplinary research challenges which need to be addressed at once. The main design challenges are GPS-denied functionality, solely onboard com
Autonomous aerial harvesting is a highly complex problem because it requires numerous interdisciplinary algorithms to be executed on mini low-powered computing devices. Object detection is one such algorithm that is compute-hungry. In this context, we make the following contributions: ( <italic xmln
We present an accurate and GPU-accelerated Stereo Visual SLAM design called Jetson-SLAM. It exhibits frame-processing rates above <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {60}$</tex-math></inline-for
This paper presents <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Neural-FxSMC</i> , a robust and precise control scheme for quadrotors to counter unknown dynamics, uncertainties, and external disturbances. <italic xmlns:mml="http://www.w3.org/1998
Channel pruning approaches for convolutional neural networks (ConvNets) deactivate the channels statically or dynamically and require special implementation. In addition channel squeezing in representative ConvNets is carried out via 1 x 1 convolutions which dominates a large portion of computations…
In this work, we propose an end-to-end Thrust Microstepping and Decoupled Control (TMDC) of quadrotors. TMDC focuses on precise off-centered aerial grasping of payloads dynamically, which are attached rigidly to the UAV body via a gripper contrary to the swinging payload. The dynamic payload graspin
Deep neural networks have demonstrated excellent object detection and segmentation performance from RGB data. However, these models can only recognize and predict segmentation masks with great accuracy when RGB data have sufficient information about the objects of interest. In this paper, we suggest…
Machine Learning (ML) classifiers have been made more robust in recent years by leveraging the graph structure between the inputs using Neural Structured Learning (NSL). However, researchers have not taken full advantage of it for the Brain-Computer Interface (BCI) classification tasks. While the tr…
The phenomenon of compounding is ubiquitous in Sanskrit. It serves for achieving brevity in expressing thoughts, while simultaneously enriching the lexical and structural formation of the language. In this work, we focus on the Sanskrit Compound Type Identification (SaCTI) task, where we consider th…
Sanskrit Word Segmentation (SWS) is essential in making digitized texts available and in deploying downstream tasks. It is, however, non-trivial because of the sandhi phenomenon that modifies the characters at the word boundaries, and needs special treatment. Existing lexicon driven approaches for S…
The ubiquitous presence of non-stationarities in the EEG signals significantly perturb the feature distribution thus deteriorating the performance of Brain Computer Interface. In this work, a novel method is proposed based on Joint Approximate Diagonalization (JAD) to optimize stationarity for multi…
This paper is concerned with the optimal kinematic control of a robot manipulator where the robot end effector position follows a task space trajectory. The joints are actuated with the desired velocity profile to achieve this task. This problem has been solved using a single network adaptive critic…
Dynamic Movement Primitive (DMP) which is popular for motion planning of a robot manipulator, has been adapted for a nonholonomic mobile robot to track the desired trajectory. DMP is a simple damped spring model with a forcing function, which learns the trajectory. The damped spring model attracts t…
One of the main challenges in the vision-based grasping is the selection of feasible grasp regions while interacting with novel objects. Recent approaches exploit the power of convolutional neural network (CNN) to achieve accurate grasping at the cost of high computational power and time. In this pa…
This paper proposes a fast terminal sliding mode super twisting controller (FTSMSTC) design for quadrotor position and altitude tracking in the presence of bounded disturbances. A nonlinear fast terminal sliding manifold has been proposed for fast convergence of the tracking error to zero in finite…