Showing papers in "Robotics and Autonomous Systems in 2013"

TL;DR: A review of the most successful CPP methods, focusing on the achievements made in the past decade, is presented, providing links to the most interesting and successful works.

TL;DR: A classification based on the principles through which the variable stiffness and damping are achieved is proposed and allows for designers of new devices to orientate and take inspiration and users of VIA's to be guided in the design and implementation process for their targeted application.

TL;DR: This paper provides a survey of existing approaches to human-aware navigation and offers a general classification scheme for the presented methods.

TL;DR: The Self-Adaptive Goal Generation Robust Intelligent Adaptive Curiosity (SAGG-RIAC) architecture is introduced as an intrinsically motivated goal exploration mechanism which allows active learning of inverse models in high-dimensional redundant robots.

TL;DR: A novel concept and platform is developed for multimodal Augmented Reality-based training of maintenance and assembly skills, which includes sub-skill training and the evaluation of the training system, which focuses on procedural skills and the appropriate methods for improving them.

TL;DR: The results indicate that especially the variables of usefulness, adaptability, enjoyment, sociability, companionship and perceived behavioral control are important evaluating the user acceptance of social robots.

TL;DR: An equivalent IMU factor based on a recently developed technique for IMU pre-integration is introduced, drastically reducing the number of states that must be added to the system.

TL;DR: Based on a given set of requirements these principles are examined and in terms of a comprehensive state-of-the-art more than hundred climbing robots are presented and this schematics is applied to design aspects of a wall-climbing robot which should be able to inspect large concrete buildings.

TL;DR: A core ontology that encompasses a set of terms commonly used in Robotics and Automation is introduced along with the methodology it has been adopted.

TL;DR: This paper investigates the leader-follower formation control problem for nonholonomic mobile robots based on a bioinspired neurodynamics based approach, and proposes an auxiliary angular velocity control law to guarantee the global asymptotic stability of the followers and to further guarantee the local asymPTotic Stability of the entire formation.

TL;DR: A motion controller based on the dynamical behavior of a known discrete chaotic system, the Logistic map, is presented, based on a microcontroller for realizing a chaotic random bit generator and converting the produced chaotic bit sequence, to the robot's trajectory of motion.

TL;DR: Novel algorithms that perform incremental updates that only visit cells affected by changes are presented that can be used to implement highly efficient collision checking and holonomic path planning for non-circular robots and are easy to implement.

TL;DR: The study found that, there are rich research efforts in terms of KINEMATICS, DYNAMICS, MODELING and CONTROL methodologies for robotics hand design, and there are quite large number of attempts to acquire biologically inspired hands.

TL;DR: Omniclimber, a new climbing robot with high maneuverability for inspection of ferromagnetic flat and convex human made structures and adaptability to various structures with different curvatures and materials is introduced.

TL;DR: A planner for underactuated hyper-redundant robots, such as humanoid robots, for which the movement can only be initiated by taking contacts with the environment is presented.

TL;DR: This study aims to present a novel CAD-based robot programming system accessible to anyone with basic knowledge of CAD and robotics, and shows the effectiveness and versatility of the proposed approach.

TL;DR: The necessity of developing robotics ontologies and standards focusing on the past and current research efforts is described, and a roadmap for service robotics ontology development is proposed.

TL;DR: The first technique presented is greedy and aims to maximize robot's local gain while the second one is an extension of the former, which takes into account the distribution of agents in the space to reduce interference and foster scalability.

TL;DR: The recent challenges and future trends on ambient intelligence, ubiquitous and networked robots, and cloud robotics are introduced and it is suggested that a new generation of ubirobots that enrich their cognitive capabilities and share their knowledge by connecting themselves to cloud infrastructures is needed.

TL;DR: These algorithms have been evaluated using real-world datasets from both structured and unstructured environments and benchmarked against a state-of-the-art point-based region growing (PBRG) algorithm with regard to segmentation speed.

TL;DR: The experimental results prove that adding compliance through IPMC helps in peg-in-hole assembly.

TL;DR: Two guidance laws are proposed to solve the problem of automatic path tracking by autonomous farming vehicles subject to wheel slips, and both explicitly take into account the constraints on the steering angle and ensure tracking an arbitrarily curved path.

TL;DR: This work employs incremental smoothing and mapping (iSAM) as the underlying SLAM state estimator and uses an improved appearance-based method for detecting loop closures within single mapping sessions and across multiple sessions to stitch together pose graph maps from multiple visual mapping sessions.

TL;DR: The overall result was that all participants were able to successfully operate the device, showing a high level of robustness of both, the BCI system, and the navigation system.

TL;DR: A novel method for robot navigation in dynamic environments, referred to as visibility binary tree algorithm, which relies on the construction of the set of all complete paths between robot and target to create a visibility Binary tree on top of which an algorithm for shortest path is run.

TL;DR: Probabilistic multiple hypothesis anchoring is introduced to create and maintain a semantically rich world model using probabilistic anchoring to be able to deal with ambiguous scenarios.

TL;DR: This paper reviews how a particular computational approach to movementPrimitives, called dynamic movement primitives, can contribute to learning motor skills, and addresses imitation learning, generalization, trial-and-error learning by reinforcement learning, movement recognition, and control based on movement Primitives.

TL;DR: An architecture that makes programming of robot behavior of an arbitrary complexity possible for end-users and shows the technical solutions in a way that is easy to understand and generalize to different situations is proposed.

TL;DR: The proposed approach provides a solution based on a leader-followers architecture with a prescribed formation geometry that adapts dynamically to the environment that allows the formation to react to both static and dynamic obstacles with an easily changeable behavior.

TL;DR: A syntactic approach to imitation learning that captures important task structures in the form of probabilistic activity grammars from a reasonably small number of samples under noisy conditions and can be recursively applied to help recognize unforeseen, more complicated tasks that share underlying structures.