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Unmanned Aerial Vehicles (UAVs) exhibit great agility and usually require a trained pilot to operate them, while being restricted to line-of-sight range. This prevents their wide introduction in applications such as inspection for disaster scenarios. Our goal is to enable rescue teams untrained in piloting to teleoperate a UAV as an aid to their mission, while being able to focus on the task at hand...
It is necessary for a long-range space rover to model its 3D environment in order to identify drivable roads while avoiding obstacles and hazards. We present a method of modeling a 3D environment, while identifying drivable roads and obstacles, by accumulating a sequence of point clouds from stereo. The technical issues we deal with are how to avoid error accumulation in registering point clouds using...
Agile robots, such as small Unmanned Aerial Vehicles (UAVs) can have a great impact on the automation of tasks, such as industrial inspection and maintenance or crop monitoring and fertilization in agriculture. Their deploy-ability, however, relies on the UAV's ability to self-localize with precision and exhibit robustness to common sources of uncertainty in real missions. Here, we propose a new system...
In general, robot grasping approaches are based on the usage of multi-finger grippers. However, when large size objects need to be manipulated vacuum grippers are preferred, instead of finger based grippers. This paper aims to estimate the best picking place for a two suction cups vacuum gripper, when planar objects with an unknown size and geometry are considered. The approach is based on the estimation...
3D LiDAR is widely used for mobile robots environment perception nowadays, which has high precision of distance measurement. In this paper, a calibration method which is suitable for Velodyne VLP-16 is firstly introduced. And then we utilize statistical filtering for isolated points removal. After statistical filtering, a slope location and orientation estimation method is presented based on PROSAC...
Light field cameras capture a scene's multi-directional light field with one image, allowing the estimation of depth. In this paper, we introduce a fully automatic method for depth estimation from a single plenoptic image running a RANSAC-like algorithm for feature matching. The novelty about our method is the global method to back project correspondences found using photometric similarity to obtain...
The absolute orientation problem arises often in vision and robotics. Despite that robust algorithmic solutions exist for quite some time, they all rely on matrix factorizations such as eigen or singular value decomposition. These factorizations are relatively expensive to compute, therefore might become a performance bottleneck when absolute orientation needs to be repeatedly computed on low-end...
We consider the question of benchmarking the performance of methods used for estimating the depth of a scene from a single image. We describe various measures that have been used in the past, discuss their limitations and demonstrate that each is deficient in one or more ways. We propose a new measure of performance for depth estimation that overcomes these deficiencies, and has a number of desirable...
Obstacle Detection is a central problem for any robotic system, and critical for autonomous systems that travel at high speeds in unpredictable environment. This is often achieved through scene depth estimation, by various means. When fast motion is considered, the detection range must be longer enough to allow for safe avoidance and path planning. Current solutions often make assumption on the motion...
This paper proposes a co-worker in-time Parts/tools Delivery to You robot, PaDY, in an automobile assembly line. Since co-worker robots share a workspace, the workers are at risk of colliding with them. Therefore, the safety of the workers has to be considered when operating such robots. In previous studies, the robot generally stops to ensure the worker's safety when a collision is detected, delaying...
This paper proposes a novel method for randomized bin-picking based on learning. When a two-fingered gripper tries to pick an object from the pile, a finger often contacts a neighboring object. Even if a finger contacts a neighboring object, the target object will be successfully picked depending on the configuration of neighboring objects. In our proposed method, we use the visual information on...
Fuzzy theory was motivated by the need to create human-like solutions that allow representing vagueness and uncertainty that exist in the real-world. These capabilities have been recently further enhanced by deep learning since it allows converting complex relation between data into knowledge. In this paper, we present a novel Deep-Neuro-Fuzzy strategy for unsupervised estimation of the interaction...
Measuring “how much the human is in the interaction” - the level of engagement - is instrumental in building effective interactive robots. Engagement, however, is a complex, multi-faceted cognitive mechanism that is only indirectly observable. This article formalizes with-me-ness as one of such indirect measures. With-me-ness, a concept borrowed from the field of Computer-Supported Collaborative Learning,...
The current paper addresses the problem of object identification from multiple 3D partial views, collected from different view angles with the objective of disambiguating between similar objects. We assume a mobile robot equipped with a depth sensor that autonomously grasps an object from different positions, with no previous known pattern. The challenge is to efficiently combine the set of observations...
Efficient obstacle detection is a key requirement for safe robot navigation. We consider the operation of autonomous vehicles in structured industrial environments. In such scenarios, an usual way to perform obstacle detection is to generate an estimate of the ground and detect elements that are on the path of the vehicle, using the ground as a spatial reference. For this task, 3D occupancy grids...
In this paper, we introduce a non-verbal multimodal joint visual attention model for human-robot interaction in household scenarios. Our model combines the bottom-up saliency and depth-based segmentation with the top-down cues such as pointing and gaze to detect the objects of interest according to the user. For generation of the top-down saliency maps, we have introduced novel methods for object...
In this paper, we present a monocular visual-inertial odometry algorithm which, by directly using pixel intensity errors of image patches, achieves accurate tracking performance while exhibiting a very high level of robustness. After detection, the tracking of the multilevel patch features is closely coupled to the underlying extended Kalman filter (EKF) by directly using the intensity errors as innovation...
This paper shows how to carry out batch continuous-time trajectory estimation for bodies translating and rotating in three-dimensional (3D) space, using a very efficient form of Gaussian-process (GP) regression. The method is fast, singularity-free, uses a physically motivated prior (the mean is constant body-centric velocity), and permits trajectory queries at arbitrary times through GP interpolation...
This paper investigates localization of sound sources in a real environment using a tablet device. For the localization, we use build-in sensors on a tablet device and additionally mount a cover with a microphone array. Because of the flat shape and limited sensor performance, the localization has mainly the following three issues; 1) the flat microphone array allows only azimuth estimation but elevation...
Pose estimation is an important step towards spacecraft docking with the space station, as it can make the spacecraft react to the pose change in real time and better accomplish the tracking mission. However, it is difficult to conduct the real rendezvous and docking practice due to the limitations of research conditions and the expenses. In order to facilitate the validation of the pose estimation...
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