Communication among microscopic robots (nanorobots) can coordinate their
activities for biomedical tasks. The feasibility of in vivo ultrasonic
communication is evaluated for micron-size robots broadcasting into various
types of tissues. Frequencies between 10MHz and 300MHz give the best tradeoff
between efficient acoustic generation and attenuation for communication over
distances of about 100 microns.

The six axis robots are widely used in automotive industry for their good
repeatability (as defined in the ISO92983) (painting, welding, mastic
deposition, handling etc.). In the aerospace industry, robot starts to be used
for complex applications such as drilling, riveting, fiber placement, NDT, etc.
Given the positioning performance of serial robots, precision applications
require usually external measurement device with complexes calibration
procedure in order to reach the precision needed.

RGB-D cameras, which give an RGB image to- gether with depths, are becoming
increasingly popular for robotic perception. In this paper, we address the task
of detecting commonly found objects in the 3D point cloud of indoor scenes
obtained from such cameras. Our method uses a graphical model that captures
various features and contextual relations, including the local visual
appearance and shape cues, object co-occurence relationships and geometric
relationships.

Awareness and self-awareness are two different notions related to knowing the
environment and itself. In a general context, the mechanism of self-awareness
belongs to a class of co-called "self-issues" (self-* or self-star):
self-adaptation, self-repairing, self-replication, self-development or
self-recovery. The self-* issues are connected in many ways to adaptability and
evolvability, to the emergence of behavior and to the controllability of
long-term developmental processes.

The use of mobile robots is being popular over the world mainly for
autonomous explorations in hazardous/ toxic or unknown environments. This
exploration will be more effective and efficient if the explorations in unknown
environment can be aided with the learning from past experiences. Currently
reinforcement learning is getting more acceptances for implementing learning in
robots from the system-environment interactions. This learning can be
implemented using the concept of both single-agent and multiagent.

We consider the problem of finding a control policy for a Markov Decision
Process (MDP) to maximize the probability of reaching some states while
avoiding some other states. This problem is motivated by applications in
robotics, where such problems naturally arise when probabilistic models of
robot motion are required to satisfy temporal logic task specifications. We
transform this problem into a Stochastic Shortest Path (SSP) problem and
develop a new approximate dynamic programming algorithm to solve it.

Common estimation algorithms, such as least squares estimation or the Kalman
filter, operate on a state in a state space S that is represented as a
real-valued vector. However, for many quantities, most notably orientations in
3D, S is not a vector space, but a so-called manifold, i.e. it behaves like a
vector space locally but has a more complex global topological structure. For
integrating these quantities, several ad-hoc approaches have been proposed.

During the last decade, sampling-based path planning algorithms, such as
Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have
been shown to work well in practice and possess theoretical guarantees such as
probabilistic completeness. However, little effort has been devoted to the
formal analysis of the quality of the solution returned by such algorithms,
e.g., as a function of the number of samples.

Current progresses in home automation and service robotic environment have
highlighted the need to develop interoperability mechanisms that allow a
standard communication between the two systems. During the development of the
DHCompliant protocol, the problem of locating mobile devices in an indoor
environment has been investigated. The communication of the device with the
location service has been carried out to study the time delay that web services
offer in front of the sockets.

The paper presents a methodology to enhance the stiffness analysis of
parallel manipulators with parallelogram-based linkage. It directly takes into
account the influence of the external loading and allows computing both the
non-linear ``load-deflection" relation and relevant rank-deficient stiffness
matrix. An equivalent bar-type pseudo-rigid model is also proposed to describe
the parallelogram stiffness by means of five mutually coupled virtual springs.
The contributions of this paper are highlighted with a parallelogram-type
linkage used in a manipulator from the Orthoglide family.

This paper focuses on the performance evaluation of the parallel manipulators
for milling of composite materials. For this application the most significant
performance measurements, which denote the ability of the manipulator for the
machining are defined. In this case, optimal synthesis task is solved as a
multicriterion optimization problem with respect to the geometric, kinematic,
kinetostatic, elastostostatic, dynamic properties. It is shown that stiffness
is an important performance factor.

We propose distributed algorithms to automatically deploy a group of mobile
robots to partition and provide coverage of a non-convex environment. To handle
arbitrary non-convex environments, we represent them as connected graphs. Our
partitioning and coverage algorithm requires only short-range, unreliable
pairwise "gossip" communication among the agents. The algorithm has two
components: (1) a motion protocol to ensure that each robot communicates with
its neighbors at least sporadically, and (2) a pairwise partitioning rule to
update territory ownership whenever two robots communicate.

Most commercial manufacturers of industrial robots require their robots to be
programmed in a proprietary language tailored to the domain - a typical
domain-specific language (DSL). However, these languages oftentimes suffer from
shortcomings such as controller-specific design, limited expressiveness and a
lack of extensibility. For that reason, we developed the extensible Robotics
API for programming industrial robots on top of a general-purpose language.
Although being a very flexible approach to programming industrial robots, a
fully-fledged language can be too complex for simple tasks.

Off-line robot dynamic identification methods are mostly based on the use of
the inverse dynamic model, which is linear with respect to the dynamic
parameters. This model is sampled while the robot is tracking reference
trajectories that excite the system dynamics. This allows using linear
least-squares techniques to estimate the parameters. The efficiency of this
method has been proved through the experimental identification of many
prototypes and industrial robots.

We report a globally-optimal approach to robotic path planning under
uncertainty, based on the theory of quantitative measures of formal languages.
A significant generalization to the language-measure-theoretic path planning
algorithm $\nustar$ is presented that explicitly accounts for average dynamic
uncertainties and estimation errors in plan execution.

Most cognitive architectures rely on discrete representation, both in space
(e.g., objects) and in time (e.g., events). However, a robot interaction with
the world is inherently continuous, both in space and in time. The segmentation
of the stream of perceptual inputs a robot receives into discrete and
meaningful events poses as a challenge in bridging the gap between internal
cognitive representations, and the external world.

Virtual human techniques have been used a lot in industrial design in order
to consider human factors and ergonomics as early as possible. The physical
status (the physical capacity of virtual human) has been mostly treated as
invariable in the current available human simulation tools, while indeed the
physical capacity varies along time in an operation and the change of the
physical capacity depends on the history of the work as well. Virtual Human
Status is proposed in this paper in order to assess the difficulty of manual
handling operations, especially from the physical perspective.

An accurate motion model is an important component in modern-day robotic
systems, but building such a model for a complex system often requires an
appreciable amount of manual effort. In this paper we present a motion model
representation, the Dynamic Gaussian Mixture Model (DGMM), that alleviates the
need to manually design the form of a motion model, and provides a direct means
of incorporating auxiliary sensory data into the model.

... This paper is to describe exploratory research on the design of a modular
autonomous mobile robot controller. The controller incorporates a fuzzy logic
[8] [9] approach for steering and speed control [37], a FL approach for
ultrasound sensing and an overall expert system for guidance. The advantages of
a modular system are related to portability and transportability, i.e. any
vehicle can become autonomous with minimal modifications.

FastSLAM is a framework for simultaneous localization using a
Rao-Blackwellized particle filter. In FastSLAM, particle filter is used for the
mobile robot pose (position and orientation) estimation, and an Extended Kalman
Filter (EKF) is used for the feature location's estimation. However, FastSLAM
degenerates over time. This degeneracy is due to the fact that a particle set
estimating the pose of the robot loses its diversity. One of the main reasons
for loosing particle diversity in FastSLAM is sample impoverishment.

This article synthezises the most important results on the kinematics of
cuspidal manipulators i.e. nonredundant manipulators that can change posture
without meeting a singularity. The characteristic surfaces, the uniqueness
domains and the regions of feasible paths in the workspace are defined. Then,
several sufficient geometric conditions for a manipulator to be noncuspidal are
enumerated and a general necessary and sufficient condition for a manipulator
to be cuspidal is provided. An explicit DH-parameter-based condition for an
orthogonal manipulator to be cuspidal is derived.

Sampling-based motion planners are effective means for generating
collision-free motion paths. However, the quality of these motion paths is
often notoriously low, especially in high-dimensional configuration spaces
(with respect to quality measures such as path length, clearance, smoothness or
energy). We introduce a simple and effective algorithm for merging an arbitrary
number of input motion paths into a hybrid output path of superior quality,
using a generalized formulation of path quality.

The paper focuses on the enhanced stiffness modeling of robotic manipulators
by taking into account influence of the external force/torque acting upon the
end point. It implements the virtual joint technique that describes the
compliance of manipulator elements by a set of localized six-dimensional
springs separated by rigid links and perfect joints.

It was shown recently that parallel manipulators with several inverse
kinematic solutions have the ability to avoid parallel singularities [Chablat
1998a] and self-collisions [Chablat 1998b] by choosing appropriate joint
configurations for the legs. In effect, depending on the joint configurations
of the legs, a given configuration of the end-effector may or may not be free
of singularity and collision.

This paper introduces a methodology to analyze geometrically the
singularities of manipulators, of which legs apply both actuation forces and
constraint moments to their moving platform. Lower-mobility parallel
manipulators and parallel manipulators, of which some legs do not have any
spherical joint, are such manipulators. The geometric conditions associated
with the dependency of six Pl\"ucker vectors of finite lines or lines at
infinity constituting the rows of the inverse Jacobian matrix are formulated
using Grassmann-Cayley Algebra.

This paper will provide a method to decompose forging dies for machining
planning in the case of high speed machining finishing operations. This method
lies on a machining feature approach model presented in the following paper.
The two main decomposition phases, called Basic Machining Features Extraction
and Process Planning Generation, are presented. These two decomposition phases
integrates machining resources models and expert machining knowledge to provide
an outstanding process planning.

Today's forging die manufacturing process must be adapted to several
evolutions in machining process generation: CAD/CAM models, CAM software
solutions and High Speed Machining (HSM). In this context, the adequacy between
die shape and HSM process is in the core of machining preparation and process
planning approaches. This paper deals with an original approach of machining
preparation integrating this adequacy in the main tasks carried out.

The paper presents a new stiffness modelling method for multi-chain parallel
robotic manipulators with flexible links and compliant actuating joints. In
contrast to other works, the method involves a FEA-based link stiffness
evaluation and employs a new solution strategy of the kinetostatic equations,
which allows computing the stiffness matrix for singular postures and to take
into account influence of the external forces.

In this paper we describe a new robotic brachytherapy needle-insertion system
that is designed to replace the template used in the manual technique. After a
brief review of existing robotic systems, we describe the requirements that we
based our design upon. A detailed description of the proposed system follows.
Our design is capable of positioning and inclining a needle within the same
workspace as the manual template. To help improve accuracy, the needle can be
rotated about its axis during insertion into the prostate.

This paper discusses the utility of using simple stiffness and vibrations
models, based on the Jacobian matrix of a manipulator and only the rigidity of
the actuators, whenever its geometry is optimised. In many works, these
simplified models are used to propose optimal design of robots. However, the
elasticity of the drive system is often negligible in comparison with the
elasticity of the elements, especially in applications where high dynamic
performances are needed.