Quantum Computation in Robotic Science and Applications

Petschnigg, Christina; Brandstötter, Mathias; Pichler, Horst; Hofbaur, Michael; Dieber, Bernhard

doi:10.1109/icra.2019.8793768

Cited by 34 publications

(23 citation statements)

References 64 publications

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“…Similar to this, in robotic aspect of affective computing, i.e., receiving the stimulus and after the processing to make the corresponding response, received stimuli are processed to determine the best response. Consequently, interpretations of affective computing from the quantum viewpoint, i.e., QAC, entails assimilating the mechanism of the amygdala and its role in generating and responding to emotions within the precepts of quantum mechanics [20] [21], for example, the state the amygdala is in can be represented as a vector (red arrow in Fig. 1(a)) of the two eigenstates in a Bloch sphere [9].…”

Section: Quantum Effects In Human Behaviourmentioning

confidence: 99%

Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions

Yan¹,

Iliyasu²,

Hirota³

2020

Preprint

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This study presents a modest attempt to interpret, formulate, and manipulate emotion of robots within the precepts of quantum mechanics. Our proposed framework encodes the emotion information as a superposition state whilst unitary operators are used to manipulate the transition of the emotion states which are recovered via appropriate quantum measurement operations. The framework described provides essential steps towards exploiting the potency of quantum mechanics in a quantum affective computing paradigm. Further, the emotions of multi-robots in a specified communication scenario are fused using quantum entanglement thereby reducing the number of qubits required to capture the emotion states of all the robots in the environment, and fewer quantum gates are needed to transform the emotion of all or part of the robots from one state to another. In addition to the mathematical rigours expected of the proposed framework, we present a few simulation-based demonstrations to illustrate its feasibility and effectiveness. This exposition is an important step in the transition of formulations of emotional intelligence to the quantum era.

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Section: Quantum Effects In Human Behaviourmentioning

confidence: 99%

Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions

Yan¹,

Iliyasu²,

Hirota³

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Quantum computing has been applied in robotics as a tool for speed up classical tools, or in a framework which is still the classical one [2]. Our approach is quite different: starting from the very properties of quantum systems, we studied how to exploit them in a novel, simpler framework.…”

Section: Related Workmentioning

confidence: 99%

“…It is noteworthy that only one query at a time is possible due to the quantum state collapse after any measurement[15] 2. We use the IBMQ Qiskit[17] notation rather than the one usually used in quantum…”

mentioning

confidence: 99%

Multi-sensory Integration in a Quantum-Like Robot Perception Model

Lanza,

Solinas,

Mastrogiovanni

2020

Preprint

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Formalisms inspired by Quantum theory have been used in Cognitive Science for decades. Indeed, Quantum-Like (QL) approaches provide descriptive features that are inherently suitable for perception, cognition, and decision processing. A preliminary study on the feasibility of a QL robot perception model has been carried out for a robot with limited sensing capabilities [1]. In this paper, we generalize such a model for multi-sensory inputs, creating a multidimensional world representation directly based on sensor readings. Given a 3-dimensional case study, we highlight how this model provides a compact and elegant representation, embodying features that are extremely useful for modeling uncertainty and decision. Moreover, the model enables to naturally define query operators to inspect any world state, which answers quantifies the robot's degree of belief on that state.

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“…First, employing quantum mechanics to describe emotion space presupposes the potential use of lower computing resources (since quantum parallelism offers exponential speed up relative to the required number of qubits as well as the sufficient (polynomial) number of CNOT gates that are needed to manipulate a quantum emotion, which sharply decreases the computational complexity of the process) and also quantum mechanics ensures that all transformations are unitary and reversible, so that the robot's emotion could be easily transferred (forward or backward) within the emotion space. Regarding the second question that was posed earlier, by envisioning a qubot as a mobile quantum system that includes an on-board quantum computer and its required ancilliary systems [15], it is reasonable to imagine that qubots will carry out tasks whose goals include specified changes in conformity with the state of the environment or even carrying out measurements on the environment itself [16,17]. Moreover, it is envisioned that future robots will operate in all kinds of environments: manipulating, controlling, and interacting with different sensors, which themselves capture massive amounts of data.…”

Section: Introductionmentioning

confidence: 99%

Quantum Structure for Modelling Emotion Space of Robots

et al. 2019

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Utilising the properties of quantum mechanics, i.e., entanglement, parallelism, etc., a quantum structure is proposed for representing and manipulating emotion space of robots. This quantum emotion space (QES) provides a mechanism to extend emotion interpretation to the quantum computing domain whereby fewer resources are required and, by using unitary transformations, it facilitates easier tracking of emotion transitions over different intervals in the emotion space. The QES is designed as an intuitive and graphical visualisation of the emotion state as a curve in a cuboid, so that an “emotion sensor” could be used to track the emotion transition as well as its manipulation. This ability to use transition matrices to convey manipulation of emotions suggests the feasibility and effectiveness of the proposed approach. Our study is primarily influenced by two developments. First, the massive amounts of data, complexity of control, planning and reasoning required for today’s sophisticated automation processes necessitates the need to equip robots with powerful sensors to enable them adapt and operate in all kinds of environments. Second, the renewed impetus and inevitable transition to the quantum computing paradigm suggests that quantum robots will have a role to play in future data processing and human-robot interaction either as standalone units or as part of larger hybrid systems. The QES proposed in this study provides a quantum mechanical formulation for quantum emotion as well as a platform to process, track, and manipulate instantaneous transitions in a robot’s emotion. The new perspective will open broad areas, such as applications in emotion recognition and emotional intelligence for quantum robots.

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Quantum Computation in Robotic Science and Applications

Cited by 34 publications

References 64 publications

Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions

Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions

Multi-sensory Integration in a Quantum-Like Robot Perception Model

Quantum Structure for Modelling Emotion Space of Robots

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