Ayush Dewan

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This paper presents a novel exploration strategy for coordinated exploration between unmanned ground vehicles (UGV) and micro-air vehicles (MAV). The exploration is modeled as an Integer Programming (IP) optimization problem and the allocation of the vehicles(agents) to frontier locations is modeled using binary variables. The formulation is also studied(More)
Robots are expected to operate autonomously in increasingly complex scenarios such as crowded streets or heavy traffic situations. Perceiving the dynamics of moving objects in the environment is crucial for safe and smart navigation and therefore a key enabler for autonomous driving. In this paper we present a novel model-free approach for detecting and(More)
This paper proposes a robust approach for image based floor detection and segmentation from sequence of images or video. In contrast to many previous approaches, which uses a priori knowledge of the surroundings, our method uses combination of modified sparse optical flow and planar homography for ground plane detection which is then combined with graph(More)
The perception of the dynamic aspects of the environment is a highly relevant precondition for the realization of autonomous robot system acting in the real world. In this paper, we propose a novel method for estimating dense rigid scene flow in 3D LiDAR scans. We formulate the problem as an energy minimization problem, where we assume local geometric(More)
This paper presents a novel optimization formulation for coordinated exploration between unmanned ground vehicles (UGV) and micro-aerial vehicles (MAV). The exploration is posed as an Integer Programming (IP) problem and the allotment of these vehicles(agents) to frontier locations is specified as an integer constraint. The optimization provides a one shot(More)
In this paper, we propose a novel planning technique for monocular camera based Simultaneous Localization and Mapping(VSLAM). In VSLAM, the objective is to estimate the trajectory of camera and simultaneously identify 3D feature points and build a map, using camera as a depth sensor. Unlike a laser range finder based SLAM, VSLAM is known to be erroneous(More)
Robots are expected to operate autonomously in dynamic environments. Understanding the underlying dynamic characteristics of objects is a key enabler for achieving this goal. In this paper, we propose a method for pointwise semantic classification of 3D LiDAR data into three classes: non-movable, movable and dynamic. We concentrate on understanding these(More)
Over the past couple of years, with the development of efficient control algorithms, micro aerial vehicles have come into the picture. In this paper, we consider the problem of creating a map of an indoor environment which provides more information than a 2D map and at the same time is more accurate than the contemporary 3D mapping algorithms. We propose a(More)
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