Classic task programming methods based on the specification of desired Cartesian frames can easily generate overconstrained task specifications, reducing the motion capabilities of the involved robot(s) and increasing...
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Classic task programming methods based on the specification of desired Cartesian frames can easily generate overconstrained task specifications, reducing the motion capabilities of the involved robot(s) and increasing the total programming effort. This paper presents a general constraint-based programming framework for the specification of a task as minimum set of constraints and the automatic generation of motion optimization problems. The framework can handle constraints involving both robot joint and Cartesian coordinates, as well as including explicit time dependency. The proposed formalism naturally scales to robotic applications with multiple robots, on which multiple frames might be of interest. Additionally, the paper proposes a theoretical comparison with already existing constraint-based programming methods. Finally, the validity and the effectiveness of the proposed approach is numerically supported by illustrative examples, as well as by case studies mocking real industrial setups.
This paper introduces a constraint-based specification of an object handover in order to simplify the implementation of reactive handover controllers. A number of desired robot behaviors are identified in different ph...
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ISBN:
(数字)9783030963590
ISBN:
(纸本)9783030963590;9783030963583
This paper introduces a constraint-based specification of an object handover in order to simplify the implementation of reactive handover controllers. A number of desired robot behaviors are identified in different phases of the handover and specified as constraints. The degrees-of-freedom in the reaching motion towards the tracked object, such as rotational symmetry in the object, are easily expressed with constraints and used by the controller. During the physical transfer, a desired force interaction and compliance can be specified. Deviations from the nominal behavior are also dealt with, such as breaking of the handover intent, a moving object and disturbance forces. The controller is validated on a real robot setup showcasing a bidirectional handover. Thanks to the modular approach of combining constraints the developed task specification can be easily extended with more reactive behaviors in the future.
The features of modem collaborative robots, mainly their kinematic redundancy combined with the light-weight structure, can be fully exploited in parts assembly. Traditional robot-level paradigm to robot programming, ...
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The features of modem collaborative robots, mainly their kinematic redundancy combined with the light-weight structure, can be fully exploited in parts assembly. Traditional robot-level paradigm to robot programming, that requires to explicitly specify the motion of the robot and allows to use contact forces for motion supervision only, cannot be easily applied to complex interaction tasks, such as robotic assembly. Instead, by shifting paradigm to skill-basedprogramming, it is possible to specify force control actions at task level and inherently provide compliant capabilities, without the need to specify the motions of the robot. To this end, this paper presents a constraint-based programming framework for the implementation of assembly skills for light-weight redundant robots, enabling a reactive generation of motion trajectories based on force control requirements. The effectiveness of the proposed approach is experimentally validated on a bimanual assembly use case performed with the ABB YuMi dual-arm robot, requiring a peg-in-hole insertion and a cap-rotation task. Estimation of the interaction force/torque additionally enables the execution of the assembly operation without the need for exteroceptive sensors.
Safety is the first and foremost step on our long journey to a future in which robots are moving out of the cage to collaborate with and assist people in various fields from entertainment to manufacturing. Different f...
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Safety is the first and foremost step on our long journey to a future in which robots are moving out of the cage to collaborate with and assist people in various fields from entertainment to manufacturing. Different from the well-defined structured environment, safe robot control in a workspace with moving objects, e.g. a human, requires us to control the robot motion on the fly. In order to computationally efficiently achieve a feasible solution, we propose a constraint-based programming approach to guarantee the safe human -robot interaction. We use an optimization framework to integrate constraints from two -fold: the robot control constraints that are responsible for a generic robotic task and the online formulated safety constraints that are responsible for safe human-robot interaction. In this way, we preserve the task execution ability of a robot while guarantee the safe human -robot interaction. We validate the proposed approach with a Schunk industrial manipulator. The experimental results confirms the fact that the proposed approach has the potential to enable an industrial manipulator to work with a human coworker side -by-side. (C) 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 51st CIRP Conference on Manufacturing Systems.
Safety is the first and foremost step on our long journey to a future in which robots are moving out of the cage to collaborate with and assist people in various fields from entertainment to manufacturing. Different f...
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Safety is the first and foremost step on our long journey to a future in which robots are moving out of the cage to collaborate with and assist people in various fields from entertainment to manufacturing. Different from the well-defined structured environment, safe robot control in a workspace with moving objects, e.g. a human, requires us to control the robot motion on the fly. In order to computationally efficiently achieve a feasible solution, we propose a constraint-based programming approach to guarantee the safe human-robot interaction. We use an optimization framework to integrate constraints from two-fold: the robot control constraints that are responsible for a generic robotic task and the online formulated safety constraints that are responsible for safe human-robot interaction. In this way, we preserve the task execution ability of a robot while guarantee the safe human-robot interaction. We validate the proposed approach with a Schunk industrial manipulator. The experimental results confirms the fact that the proposed approach has the potential to enable an industrial manipulator to work with a human coworker side-by-side.
In the annual winter route maintenance, transportation agencies often deploy multiple fleets of trucks for snow control and removal activities over a vast maintenance area which creates an operational problem in deter...
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In the annual winter route maintenance, transportation agencies often deploy multiple fleets of trucks for snow control and removal activities over a vast maintenance area which creates an operational problem in determining the optimal maintenance routes and fleet size. The objective of this paper is to develop a snowplow routing optimization model to enhance the efficiency of snow removal route planning. The routing optimization model was developed using vehicle routing problems, constraint-based programming, and geographic information system. The developed model was applied to optimize the snow removal route planning practice of a District in Kansas, United States, as a case study. The result of this study shows that the optimization model can help minimize the fleet size and increase the level of service for treating snow routes within the selected District. The results of this study are expected to assist transportation agencies in optimizing their snow route removal in winter maintenance operations.
(Semi-) autonomous complex UAV missions, such as inspection or search-and-rescue in uncertain dynamic environments, require obstacle avoidance and operator shared control. Combining humans' cognitive abilities wit...
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ISBN:
(纸本)9781467393331
(Semi-) autonomous complex UAV missions, such as inspection or search-and-rescue in uncertain dynamic environments, require obstacle avoidance and operator shared control. Combining humans' cognitive abilities with fast automation is the key for such missions. This paper presents a flight control system architecture based on the instantaneous Task Specification using constraints (iTaSC) methodology and software framework. iTaSC is a flexible constraint-based programming approach that generates a robot motion at runtime which automatically derives the input for a low-level controller taking into account constraints and intentions from the operator, obstacles and mission constraints. This setup is experimentally validated by navigating a multirotor UAV safely through a GPS-denied corridor using (intuitive) shared control with a pilot. In addition to the pilot's commands, automatic obstacle avoidance and object tracking are performed real-time through various onboard sensors and with limited onboard computational power.
In metabolic engineering, modification of metabolic networks is an important biotechnology and a challenging computational task. In the metabolic network modification, we should modify metabolic networks by newly addi...
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In metabolic engineering, modification of metabolic networks is an important biotechnology and a challenging computational task. In the metabolic network modification, we should modify metabolic networks by newly adding enzymes or/and knocking-out genes to maximize the biomass production with minimum side-effect. In this mini-review, we briefly review constraint-based formalizations for Minimum Reaction Cut (MRC) problem where the minimum set of reactions is deleted so that the target compound becomes non-producible from the view point of the flux balance analysis (FBA), elementary mode (EM), and Boolean models. Minimum Reaction Insertion (MRI) problem where the minimum set of reactions is added so that the target compound newly becomes producible is also explained with a similar formalization approach. The relation between the accuracy of the models and the risk of overfitting is also discussed. (C) 2015 Tamura et al. Published by Elsevier B.V.
Building a meaningful model of biological regulatory network is usually done by specifying the components (e.g. the genes) and their interactions, by guessing the values of parameters, by comparing the predicted behav...
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Building a meaningful model of biological regulatory network is usually done by specifying the components (e.g. the genes) and their interactions, by guessing the values of parameters, by comparing the predicted behaviors to the observed ones, and by modifying in a trial-error process both architecture and parameters in order to reach an optimal fitness. We propose here a different approach to construct and analyze biological models avoiding the trial-error part, where structure and dynamics are represented as formal constraints. We apply the method to Hopfield-like networks, a formalism often used in both neural and regulatory networks modeling. The aim is to characterize automatically the set of all models consistent with all the available knowledge (about structure and behavior). The available knowledge is formalized into formal constraints. The latter are compiled into Boolean formula in conjunctive normal form and then submitted to a Boolean satisfiability solver. This approach allows to formulate a wide range of queries, expressed in a high level language, and possibly integrating formalized intuitions. In order to explore its potential, we use it to find cycles for 3-nodes networks and to determine the flower morphogenesis regulatory network of Arabidopsis thaliana. Applications of this technique are numerous and concern the building of models from data as well as the design of biological networks possessing specified behaviors.
This paper shows the application of a generic constraint-based task specification approach for sensor-based robot systems to a laser tracing example. Key properties of the used approach are (i) its ability to specify ...
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ISBN:
(纸本)9781424408122
This paper shows the application of a generic constraint-based task specification approach for sensor-based robot systems to a laser tracing example. Key properties of the used approach are (i) its ability to specify complex robot tasks by introducing auxiliary task-oriented feature coordinates, defined with respect to user-defined object and feature frames, (ii) its support for both underconstrained and overconstrained robot tasks, and (iii) its ability to integrate sensor measurements in a unified way, using auxiliary uncertainty coordinates, to estimate geometric uncertainties in the robot system or its environment. Simulation and real world experimental results are presented.
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