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We present a novel efficient method addressing the inverse differential kinematics problem for redundant manipulators in the presence of different hard bounds (joint range, velocity, and acceleration limits) on the joint space motion. The proposed SNS (Saturation in the Null Space) iterative algorithm proceeds by successively discarding the use of joints that would exceed their motion bounds when...
This paper focuses on reducing the computational complexity of the extended Kalman filter (EKF)-based multi-robot cooperative localization (CL) by taking advantage of the sparse structure of the measurement Jacobian matrix H. In contrast to the standard EKF update, whose complexity is up to O(N4) (N is the number of robots in a team), we introduce a Modified Householder QR algorithm which fully exploits...
This paper experimentally investigates the optimization of directional dry adhesives that can be used for robotic climbing and gripping applications. Directional dry adhesives are modeled on gecko setae. The adhesives are comprised of arrays of micro-scale polymer stalks. The geometry of the polymer stalks has a significant effect upon their adhesion properties. A set of parameters including stalk...
This article addresses the problem of imagebased localization in indoor environments. The localization is achieved by querying a database of omnidirectional images that constitutes a detailed visual map of the building where the robot operates. Omnidirectional cameras have the advantage, when compared to standard perspectives, of capturing in a single frame the entire visual content of a room. This,...
This paper describes a scalable method for parallelizing sampling-based motion planning algorithms. It subdivides configuration space (C-space) into (possibly overlapping) regions and independently, in parallel, uses standard (sequential) sampling-based planners to construct roadmaps in each region. Next, in parallel, regional roadmaps in adjacent regions are connected to form a global roadmap. By...
The RRT* algorithm has recently been proposed as an optimal extension to the standard RRT algorithm [1]. However, like RRT, RRT* is difficult to apply in problems with complicated or underactuated dynamics because it requires the design of a two domain-specific extension heuristics: a distance metric and node extension method. We propose automatically deriving these two heuristics for RRT* by locally...
Off-line robot dynamic identification methods are based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint forces/torques that are linear in relation to the dynamic parameters, and on the use of linear least squares technique to calculate the parameters (IDIM-LS technique). The joint forces/torques are calculated as the product of the known control signal (the...
In this paper, we propose a Markov Chain Monte Carlo (MCMC) sampling method with the data-driven proposal distribution for six-degree-of-freedom (6-DoF) SLAM. Recently, visual odometry priors have been widely used as the process model in the SLAM formulation to improve the SLAM performance. However, modeling the uncertainties of incremental motions estimated by visual odometry is especially difficult...
This paper presents a method for pairwise 3D alignment which solves data association by matching scan segments across scans. Generating accurate segment associations allows to run a modified version of the Iterative Closest Point (ICP) algorithm where the search for point-to-point correspondences is constrained to associated segments. The novelty of the proposed approach is in the segment matching...
Transport of individual cells or chemical payloads on a subcellular scale is an enabling tool for the study of cellular communication, cell migration, and other localized phenomena. We present a magnetically actuated robotic system for the fully automated manipulation of cells and microbeads. Our strategy uses autofluorescent robotic transporters and fluorescently labeled microbeads to aid tracking...
Inverse reinforcement learning (IRL) is the task of learning the reward function of a Markov Decision Process (MDP) given knowledge of the transition function and a set of expert demonstrations. While many IRL algorithms exist, Bayesian IRL [1] provides a general and principled method of reward learning by casting the problem in the Bayesian inference framework. However, the algorithm as originally...
This study identifies the basic general perspectives that ordinary people use to evaluate humanoids (Study 1). In addition, it develops a new psychological scale to quantify general impressions regarding humanoids based on these basic perspectives (Study 2). In Study 1, to discover the basic perspectives toward humanoids, we used 11 humanoids and collected data from 919 Japanese people ranging from...
Previously we showed how delay communication between globally coupled self-propelled agents causes new spatio-temporal patterns to arise when the delay coupling is fixed among all agents [1]. In this paper, we show how discrete, randomly distributed delays affect the dynamical patterns. In particular, we investigate how the standard deviation of the time delay distribution affects the stability of...
In this paper we focus on the problem of visual odometry, i.e., the task of tracking the pose of a moving platform using visual measurements. In recent years, several VO algorithms have been proposed that employ nonlinear minimization in a sliding window of poses for this task. Through the use of iterative re-linearization, these methods are capable of successfully addressing the nonlinearity of the...
We present a method of utilizing depth information as provided by RGBD sensors for robust real-time visual simultaneous localisation and mapping (SLAM) by augmenting monocular visual SLAM to take into account depth data. This is implemented based on the feely available software “Parallel Tracking and Mapping” by Georg Klein. Our modifications allow PTAM to be used as a 6D visual SLAM system even without...
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