24 research outputs found
Robotic perception and control for a demolition task in unstructured environments
The construction industry is a capital-intensive sector that has steadily turned towards mechanized and automated solutions in the last few decades. However, due to some specificities of this field, it is still technologically behind other sectors, like manufacturing: there is room for improvements, that could lead to economical, technical, and also social benefits.
In this work we focus on demolition robotics: taking the task of demolishing a wall as a case study (related to the needs of an industrial partner of our laboratory), we propose a mockup for studying perceptual and control aspects on a scaled-down representative scenario. The thesis deals with several aspects of the demolition task, ranging from perception, to planning, to human-robot interaction (HRI). In addition to a conceptual framework, we propose some new approaches to scene segmentation and situational awareness in unstructured environments, as well as an intuitive on-site HRI paradigm
An intelligent system for electrical energy management in buildings
Recent studies have highlighted that a significant part of the electrical energy consumption in residential and business buildings is due to an improper use of the electrical appliances. In this context, an automated power management system - capable of reducing energy wastes while preserving the perceived comfort level - would be extremely appealing. To this aim, we propose GreenBuilding, a sensor-based intelligent system that monitors the energy consumption and automatically controls the behavior of appliances used in a building. GreenBuilding has been implemented as a prototype and has been experimented in a real household scenario. The analysis of the experimental results highlights that GreenBuilding is able to provide significant energy savings
A Minimal Developmental Model Can Increase Evolvability in Soft Robots
Different subsystems of organisms adapt over many time scales, such as rapid
changes in the nervous system (learning), slower morphological and neurological
change over the lifetime of the organism (postnatal development), and change
over many generations (evolution). Much work has focused on instantiating
learning or evolution in robots, but relatively little on development. Although
many theories have been forwarded as to how development can aid evolution, it
is difficult to isolate each such proposed mechanism. Thus, here we introduce a
minimal yet embodied model of development: the body of the robot changes over
its lifetime, yet growth is not influenced by the environment. We show that
even this simple developmental model confers evolvability because it allows
evolution to sweep over a larger range of body plans than an equivalent
non-developmental system, and subsequent heterochronic mutations 'lock in' this
body plan in more morphologically-static descendants. Future work will involve
gradually complexifying the developmental model to determine when and how such
added complexity increases evolvability
Evolving soft locomotion in aquatic and terrestrial environments: effects of material properties and environmental transitions
Designing soft robots poses considerable challenges: automated design
approaches may be particularly appealing in this field, as they promise to
optimize complex multi-material machines with very little or no human
intervention. Evolutionary soft robotics is concerned with the application of
optimization algorithms inspired by natural evolution in order to let soft
robots (both morphologies and controllers) spontaneously evolve within
physically-realistic simulated environments, figuring out how to satisfy a set
of objectives defined by human designers. In this paper a powerful evolutionary
system is put in place in order to perform a broad investigation on the
free-form evolution of walking and swimming soft robots in different
environments. Three sets of experiments are reported, tackling different
aspects of the evolution of soft locomotion. The first two sets explore the
effects of different material properties on the evolution of terrestrial and
aquatic soft locomotion: particularly, we show how different materials lead to
the evolution of different morphologies, behaviors, and energy-performance
tradeoffs. It is found that within our simplified physics world stiffer robots
evolve more sophisticated and effective gaits and morphologies on land, while
softer ones tend to perform better in water. The third set of experiments
starts investigating the effect and potential benefits of major environmental
transitions (land - water) during evolution. Results provide interesting
morphological exaptation phenomena, and point out a potential asymmetry between
land-water and water-land transitions: while the first type of transition
appears to be detrimental, the second one seems to have some beneficial
effects.Comment: 37 pages, 22 figures, currently under review (journal
Contest-Driven Soft-Robotics Boost: The RoboSoft Grand Challenge
This paper reports the design process, the implementation and the results of a novel robotic contest addressing soft robots, named RoboSoft Grand Challenge. Application-oriented tasks were proposed in three different scenarios where soft robotics is particularly lively: manipulation, terrestrial and underwater locomotion. Starting from about sixty expressions of interest submitted by international teams distributed across the world, nineteen robots were eventually selected to participate in the challenge in two of the initially proposed scenarios, i.e. manipulation and terrestrial locomotion. Results highlight both the effectiveness and limitations of state of the art soft robots with respect to the selected tasks. The paper will also focus on some of the advantages and disadvantages of contests as technology-steering mechanisms, including what we called "reductionist design", a phenomenon in which simplistic solutions are devised to purposely tackle the proposed tasks, possibly hindering more general and desired technological advancements
Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants
In this paper, a comprehensive methodology and simulation framework will be reviewed, designed in order to study the emergence of adaptive and intelligent behavior in generic soft-bodied creatures. By incorporating artificial evolutionary and developmental processes, the system allows to evolve complete creatures (brain, body, developmental properties, sensory, control system, etc.) for different task environments. Whether the evolved creatures will resemble animals or plants is in general not known a priori, and depends on the specific task environment set up by the experimenter. In this regard, the system may offer a unique opportunity to explore differences and similarities between these two worlds. Different material properties can be simulated and optimized, from a continuum of soft/stiff materials, to the interconnection of heterogeneous structures, both found in animals and plants alike. The adopted genetic encoding and simulation environment are particularly suitable in order to evolve distributed sensory and control systems, which play a particularly important role in plants. After a general description of the system some case studies will be presented, focusing on the emergent properties of the evolved creatures. Particular emphasis will be on some unifying concepts that are thought to play an important role in the emergence of intelligent and adaptive behavior across both the animal and plant kingdoms, such as morphological computation and morphological developmental plasticity. Overall, with this paper, we hope to draw attention on set of tools, methodologies, ideas and results, which may be relevant to researchers interested in plant-inspired robotics and intelligence
Material properties affect evolution's ability to exploit morphological computation in growing soft-bodied creatures
The concept of morphological computation holds that the
body of an agent can, under certain circumstances, exploit
the interaction with the environment to achieve useful behavior,
potentially reducing the computational burden of
the brain/controller. The conditions under which such phenomenon
arises are, however, unclear. We hypothesize that
morphological computation will be facilitated by body plans
with appropriate geometric, material, and growth properties,
while it will be hindered by other body plans in which one or
more of these three properties is not well suited to the task.
We test this by evolving the geometries and growth processes
of soft robots, with either manually-set softer or stiffer material
properties. Results support our hypothesis: we find that
for the task investigated, evolved softer robots achieve better
performances with simpler growth processes than evolved
stiffer ones. We hold that the softer robots succeed because
they are better able to exploit morphological computation.
This four-way interaction among geometry, growth, material
properties and morphological computation is but one example
phenomenon that can be investigated using the system here
introduced, that could enable future studies on the evolution
and development of generic soft-bodied creatures
Indoor channel characterization for future 5G applications
The shortage of frequency band below 6 GHz available for communications and data transfer has recently fostered the interest toward the millimeter wave (mmW) spectrum. In fact, mmW carrier frequencies allow for larger bandwidth allocations thus higher data transfer rates. It is therefore useful to evaluate the channel propagation properties of mmW within an indoor environment. In particular, the statistical parameters such as path loss exponent and shadowing have been examined by using a reliable numerical solver based on a ray-tracing (RT) technique. The results for both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions at 28 GHz and 72 GHz are reported for the case of an office environment