203 research outputs found
Two-fingered Hand with Gear-type Synchronization Mechanism with Magnet for Improved Small and Offset Objects Grasping: F2 Hand
A problem that plagues robotic grasping is the misalignment of the object and
gripper due to difficulties in precise localization, actuation, etc.
Under-actuated robotic hands with compliant mechanisms are used to adapt and
compensate for these inaccuracies. However, these mechanisms come at the cost
of controllability and coordination. For instance, adaptive functions that let
the fingers of a two-fingered gripper adapt independently may affect the
coordination necessary for grasping small objects. In this work, we develop a
two-fingered robotic hand capable of grasping objects that are offset from the
gripper's center, while still having the requisite coordination for grasping
small objects via a novel gear-type synchronization mechanism with a magnet.
This gear synchronization mechanism allows the adaptive finger's tips to be
aligned enabling it to grasp objects as small as toothpicks and washers. The
magnetic component allows this coordination to automatically turn off when
needed, allowing for the grasping of objects that are offset/misaligned from
the gripper. This equips the hand with the capability of grasping light,
fragile objects (strawberries, creampuffs, etc) to heavy frying pan lids, all
while maintaining their position and posture which is vital in numerous
applications that require precise positioning or careful manipulation.Comment: 8 pages. Accepted at IEEE IROS 2023. An accompanying video is
available at https://www.youtube.com/watch?v=RAO7Qb2ZGN
A Double Jaw Hand Designed for Multi-object Assembly
This paper presents a double jaw hand for industrial assembly. The hand
comprises two orthogonal parallel grippers with different mechanisms. The inner
gripper is made of a crank-slider mechanism which is compact and able to firmly
hold objects like shafts. The outer gripper is made of a parallelogram that has
large stroke to hold big objects like pulleys. The two grippers are connected
by a prismatic joint along the hand's approaching vector. The hand is able to
hold two objects and perform in-hand manipulation like pull-in (insertion) and
push-out (ejection). This paper presents the detailed design and implementation
of the hand, and demonstrates the advantages by performing experiments on two
sets of peg-in-multi-hole assembly tasks as parts of the World Robot Challenge
(WRC) 2018 using a bimanual robot
Laboratory Automation: Precision Insertion with Adaptive Fingers utilizing Contact through Sliding with Tactile-based Pose Estimation
Micro well-plates are commonly used apparatus in chemical and biological
experiments that are a few centimeters in thickness with wells in them. The
task we aim to solve is to place (insert) them onto a well-plate holder with
grooves a few millimeters in height. Our insertion task has the following
facets: 1) There is uncertainty in the detection of the position and pose of
the well-plate and well-plate holder, 2) the accuracy required is in the order
of millimeter to sub-millimeter, 3) the well-plate holder is not fastened, and
moves with external force, 4) the groove is shallow, and 5) the width of the
groove is small. Addressing these challenges, we developed a) an adaptive
finger gripper with accurate detection of finger position (for (1)), b) grasped
object pose estimation using tactile sensors (for (1)), c) a method to insert
the well-plate into the target holder by sliding the well-plate while
maintaining contact with the edge of the holder (for (2-4)), and d) estimating
the orientation of the edge and aligning the well-plate so that the holder does
not move when maintaining contact with the edge (for (5)). We show a
significantly high success rate on the insertion task of the well-plate, even
though under added noise.
An accompanying video is available at the following link:
https://drive.google.com/file/d/1UxyJ3XIxqXPnHcpfw-PYs5T5oYQxoc6i/view?usp=sharingComment: 7 pages, 5 figure
Development of PVDF tactile dynamic sensing in a behaviour-based assembly robot
The research presented in this thesis focuses on the development of tactile event sig¬
nature sensors and their application, especially in reactive behaviour-based robotic
assembly systems.In pursuit of practical and economic sensors for detecting part contact, the application
ofPVDF (polyvinylidene fluoride) film, a mechanical vibration sensitive piezo material,
is investigated. A Clunk Sensor is developed which remotely detects impact vibrations,
and a Push Sensor is developed which senses small changes in the deformation of a
compliant finger surface. The Push Sensor is further developed to provide some force
direction and force pattern sensing capability.By being able to detect changes of state in an assembly, such as a change of contact
force, an assembly robot can be well informed of current conditions. The complex
structure of assembly tasks provides a rich context within which to interpret changes
of state, so simple binary sensors can conveniently supply a lot more information than
in the domain of mobile robots. Guarded motions, for example, which require sensing a
change of state, have long been recognised as very useful in part mating tasks. Guarded
motions are particularly well suited to be components of assembly behavioural modules.In behaviour-based robotic assembly systems, the high level planner is endowed with
as little complexity as possible while the low level planning execution agent deals with
actual sensing and action. Highly reactive execution agents can provide advantages by
encapsulating low level sensing and action, hiding the details of sensori-motor complexity from the higher levels.Because behaviour-based assembly systems emphasise the utility of this kind of quali¬
tative state-change sensor (as opposed to sensors which measure physical quantities),
the robustness and utility of the Push Sensor was tested in an experimental behaviourbased system. An experimental task of pushing a ring along a convoluted stiff wire is
chosen, in which the tactile sensors developed here are aided by vision. Three differ¬
ent methods of combining these different sensors within the general behaviour-based
paradigm are implemented and compared. This exercise confirms the robustness and
utility of the PVDF-based tactile sensors. We argue that the comparison suggests
that for behaviour-based assembly systems using multiple concurrent sensor systems,
bottom-level motor control in terms of force or velocity would be more appropriate
than positional control. Behaviour-based systems have traditionally tried to avoid
symbolic knowledge. Considering this in the light of the above work, it was found
useful to develop a taxonomy of type of knowledge and refine the prohibition
Basic set of behaviours for programming assembly robots
We know from the well established Church-Turing thesis that any computer programÂming language needs just a limited set of commands in order to perform any computable process. However, programming in these terms is so very inconvenient that a larger set of machine codes need to be introduced and on top of these higher programming languages are erected.In Assembly Robotics we could theoretically formulate any assembly task, in terms of moves. Nevertheless, it is as tedious and error prone to program assemblies at this low level as it would be to program a computer by using just Turing Machine commands.An interesting survey carried out in the beginning of the nineties showed that the most common assembly operations in manufacturing industry cluster in just seven classes. Since the research conducted in this thesis is developed within the behaviour-based assembly paradigm which views every assembly task as the external manifestation of the execution of a behavioural module, we wonder whether there exists a limited and ergonomical set of elementary modules with which to program at least 80% of the most common operations.IIn order to investigate such a problem, we set a project in which, taking into account the statistics of the aforementioned survey, we analyze the experimental behavioural decomposition of three significant assembly tasks (two similar benchmarks, the STRASS assembly, and a family of torches). From these three we establish a basic set of such modules.The three test assemblies with which we ran the experiments can not possibly exhaust ah the manufacturing assembly tasks occurring in industry, nor can the results gathered or the speculations made represent a theoretical proof of the existence of the basic set. They simply show that it is possible to formulate different assembly tasks in terms of a small set of about 10 modules, which may be regarded as an embryo of a basic set of elementary modules.Comparing this set with Kondoleon’s tasks and with Balch’s general-purpose robot routines, we observed that ours was general enough to represent 80% of the most comÂmon manufacturing assembly tasks and ergonomical enough to be easily used by human operators or automatic planners. A final discussion shows that it would be possible to base an assembly programming language on this kind of set of basic behavioural modules
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