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The article focuses on the development of an on-board system design method for optimal control of an autonomous mobile group of objects. It is assumed that the group consists of a leader and some agents. A new method for the synthesis of an optimal multivariable control system, which is needed for preserving desired position of the agent relatively to the leader was substantiated in the article. The...
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...
A decentralized fault diagnosis and accommodation scheme in discrete time for teams of cooperative mobile robots is presented. Each vehicle estimates, via a local observer, the overall state of the team, which is used to compute its local control input and a set of residual vectors. Each residual is sensible to a fault occurring on a single teammate, even not in direct communication, and the fault...
High-gain proportional-integral-derivative (PID) position control can achieve stiff position control but it involves the risk of overshoots in some cases such as discontinuous position commands and disturbances. This paper presents a new position controller that achieves accurate trajectory tracking and overdamped resuming motion from large positional errors and disturbances. The proposed controller...
To address the safety issues in human robot interactions (HRI), a safe set algorithm (SSA) was developed previously. However, during HRI, the uncertainty levels are changing in different phases of the interaction, which is not captured by SSA. A safe exploration algorithm (SEA) is proposed in this paper to address the uncertainty levels in the robot control. To estimate the uncertainty levels online,...
This paper investigates the behavior of central Jacobi differentiator in robot identification applications. Jacobi differentiator is a Jacobi orthogonal based algebraic differentiator. It is applied to compute acceleration from noisy position measurements. Moreover, its frequency domain property is analyzed via a finite impulse response (FIR) filter point of view, indicating clearly the differentiators...
In this paper, we apply inverse optimal control approaches in order to recover the cost function that can explain given observations, for a class of constrained optimization problems. The inverse optimal control was recently solved in an approximately optimal framework, meaning that the interest is in finding the proper criteria suitable for the system for which the decisions are approximately optimal...
In order for robots to be useful in real world learning scenarios, non-expert human teachers must be able to interact with and teach robots in an intuitive manner. One essential robot capability is wide-area (mobile or nonstationary) pick-and-place tasks. Even in its simplest form, pick-and-place is a hard problem due to uncertainty arising from noisy input demonstrations and non-deterministic real...
This paper deals with development of Robust Moving Object Detection method using Visible Spectrum and Thermal Imaging. If we fuse visible spectrum and Thermal imaging together, more information about the moving object can be obtained as both are inherently complementary to each other. The segmentation of moving objects in corresponding video frames involves ‘Background Subtraction’ method. Here each...
Automatic robot / Computed Tomography (CT) scanner registration is an important feature for robot-assisted percutaneous needle placement under CT-scanner. This registration can be done using 3D images, but for fast, low X-ray radiation it is interesting to be able to perform the registration with a single slice. In this paper, a new marker is proposed, which allows to estimate the pose of a device...
This paper proposes a position control scheme that is suitable for the use as the internal position servo of an admittance controller. The proposed controller is characterized by four points: (a) PDD2 (proportional, derivative, and second derivative) feedback, (b) dither-based friction compensation, (c) sliding-mode-based noise filtering, and (d) variable D2 gain. The PDD2 structure and the friction...
Building accurate bathymetries of the seabed has been a focus of study in the last decade. For this purpose seabed point cloud registration has been a focus for some researchers. Some of this registration methods are based on gathering the points of the cloud that contain more information for the registration (i.e. the ones that flat or smooth, normally being the seabed) and using them as part of...
The segmentation of seemingly continuous movements into segments has been theorized for many years. These segments may be considered as “primitive” movements, or building blocks of more complex movements. The existence of these fragments, or sub-movements as they are called, has been supported by a wide range of studies over the past 100 years. Evidence for the existence of discrete sub-movements...
Conducting hardware experiment is often expensive in various aspects such as potential damage to the robot and the number of people required to operate the robot safely. Computer simulation is used in place of hardware in such cases, but it suffers from so-called simulation bias in which policies tuned in simulation do not work on hardware due to differences in the two systems. Model-free methods...
In this paper, we consider the problem of tracking a reference trajectory for a simplified car model based on unicycle kinematics, whose position only is measured, and where the control input and the measurements are corrupted by independent Gaussian noises. To tackle this problem we devise a novel observer-controller: the invariant Linear Quadratic Gaussian controller (ILQG). It is based on the Linear...
Dynamic Movement Primitives (DMPs) are a common method for learning a control policy for a task from demonstration. This control policy consists of differential equations that can create a smooth trajectory to a new goal point. However, DMPs only have a limited ability to generalize the demonstration to new environments and solve problems such as obstacle avoidance. Moreover, standard DMP learning...
In this paper, a distributed approach for the estimation of kinematic and inertial parameters of an unknown rigid body is presented. The body is manipulated by a pool of ground mobile manipulators. Each robot retrieves a noisy measurement of its velocity and the contact forces applied to the body. Kinematics and dynamics arguments are used to distributively estimate the relative positions of the contact...
This paper proposes a novel approach to generate trajectories that generalize given demonstrations according to optimality criteria. By formulating the problem as a quadratic program we can efficiently incorporate constraints to adapt to new desired motion requirements while achieving the main goal of matching the acceleration profile of the demonstration. This makes our method particularly suited...
We focus on the problem of speech recognition in the presence of nonstationary sudden noise, which is very likely to happen in home environments. To handle this problem, a model compensation method based on a factorial hidden Markov model (FHMM) has been recently introduced. In this architecture, speech and noise processes are modeled in parallel by a phoneme FHMM that is built by combining a clean-speech...
We propose a novel sparse representation for heavily underdetermined multichannel sound mixtures, i.e., with much more sources than microphones. The proposed approach operates in the complex Fourier domain, thus preserving spatial characteristics carried by phase differences. We derive a generalization of K-SVD which jointly estimates a dictionary capturing both spectral and spatial features, a sparse...
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