Related papers: Target State Estimation and Prediction for High Sp…
This work presents a scalable control framework based on nonlinear Model Predictive Control for high-dimensional dynamical systems. The proposed approach addresses the key challenges of model scalability and partial observability by…
We present Kalman-filter Assisted Reinforcement Learner (KARL) for dynamic object tracking and grasping over eye-on-hand (EoH) systems, significantly expanding such systems capabilities in challenging, realistic environments. In comparison…
We propose a probabilistic filtering method which fuses joint measurements with depth images to yield a precise, real-time estimate of the end-effector pose in the camera frame. This avoids the need for frame transformations when using it…
Joint estimation of grasped object pose and extrinsic contacts is central to robust and dexterous manipulation. In this paper, we propose a novel state-estimation algorithm that jointly estimates contact location and object pose in 3D using…
Motion prediction for intelligent vehicles typically focuses on estimating the most probable future evolutions of a traffic scenario. Estimating the gap acceptance, i.e., whether a vehicle merges or crosses before another vehicle with the…
This paper presents a prediction algorithm that estimates the vehicle trajectory every five milliseconds for an autonomous vehicle. A kinematic and a dynamic bicycle model are compared, with the dynamic model exhibiting superior accuracy at…
A Markov decision process-based state switching is devised, implemented, and analyzed for proximity operations of various autonomous vehicles. The framework contains a pose estimator along with a multi-state guidance algorithm. The unified…
This paper presents a general purpose framework for autonomous, vision-based interception of dynamic, non-cooperative targets, validated across three distinct mobility platforms: an unmanned aerial vehicle (UAV), a four-wheeled ground…
A unique approach for the mid-air autonomous aerial interception of non-cooperating UAV by a flying robot equipped with a net is presented in this paper. A novel interception guidance method dubbed EPN is proposed, designed to catch agile…
This paper addresses the problem of traffic prediction and control of autonomous vehicles on highways. A modified Interacting Multiple Model Kalman filter algorithm is applied to predict the motion behavior of the traffic participants by…
This paper presents a generic motion model to capture mobile robots' dynamic behaviors (translation and rotation). The model is based on statistical models driven by white random processes and is formulated into a full state estimation…
This paper investigates vision-based cooperative estimation of a 3D target object pose for visual sensor networks. In our previous works, we presented an estimation mechanism called networked visual motion observer achieving averaging of…
This work is devoted to the problem of distributed target tracking when a team of robots detect the target through a variable perception-latency mechanism. A reference for the robots to track is constructed in terms of a desired formation…
Self-driving cars and other autonomous vehicles need to detect and track objects in camera images. We present a simple online tracking algorithm that is based on a constant velocity motion model with a Kalman filter, and an assignment…
In the field of sensor fusion and state estimation for object detection and localization, ensuring accurate tracking in dynamic environments poses significant challenges. Traditional methods like the Kalman Filter (KF) often fail when…
Intercepting fast moving objects, by its very nature, is challenging because of its tight time constraints. This problem becomes further complicated in the presence of sensor noise because noisy sensors provide, at best, incomplete…
In this paper we propose a Kalman filter aided saliency detection model which is based on the conjecture that salient regions are considerably different from our "visual expectation" or they are "visually surprising" in nature. In this…
Event cameras are bioinspired sensors with reaction times in the order of microseconds. This property makes them appealing for use in highly-dynamic computer vision applications. In this work,we explore the limits of this sensing technology…
Gaze target detection aims to predict the image location where the person is looking and the probability that a gaze is out of the scene. Several works have tackled this task by regressing a gaze heatmap centered on the gaze location,…
A framework for tightly integrated motion mode classification and state estimation in motion-constrained inertial navigation systems is presented. The framework uses a jump Markov model to describe the navigation system's motion mode and…