All Outputs (15)

Short-term motion prediction of autonomous vehicles in complex environments: A Deep Learning approach (2024)
Thesis
Dulian, . A. Short-term motion prediction of autonomous vehicles in complex environments: A Deep Learning approach. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/4625808

Complex environments manifest a high level of complexity and it is of critical importance that the safety systems embedded within autonomous vehicles (AVs) are able to accurately anticipate short-term future motion of agents in close proximity. This... Read More about Short-term motion prediction of autonomous vehicles in complex environments: A Deep Learning approach.

The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation (2022)
Data
Chang, Y., Cheng, Y., Murray, J., Huang, S., & Shi, G. (2022). The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation. [Dataset]

The dataset contains image samples and Multi-task labels (i.e., regression and classification labels) collected from onboard UAV sensors in real-world indoor environments. By transforming the original labels following the instructions at: https://git... Read More about The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation.

Virtual reality crowd simulation: effects of agent density on user experience and behaviour (2018)
Journal Article
Dickinson, P., Gerling, K., Hicks, K., Murray, J., Shearer, J., & Greenwood, J. (2019). Virtual reality crowd simulation: effects of agent density on user experience and behaviour. Virtualreality : the journal of the Virtual Reality Society, 23(1), 19-32. https://doi.org/10.1007/s10055-018-0365-0

Agent-based crowd simulations are used for modelling building and space usage, allowing designers to explore hypothetical real-world scenarios, including extraordinary events such as evacuations. Existing work which engages virtual reality (VR) as a... Read More about Virtual reality crowd simulation: effects of agent density on user experience and behaviour.

Perception of artificial conspecifics by bearded dragons (Pogona vitticeps) (2018)
Journal Article
Frohnwieser, A., Pike, T. W., Murray, J. C., & Wilkinson, A. (2019). Perception of artificial conspecifics by bearded dragons (Pogona vitticeps). Integrative Zoology, 14(2), 214-222. https://doi.org/10.1111/1749-4877.12303

Artificial animals are increasingly used as conspecific stimuli in animal behavior research. However, researchers often have an incomplete understanding of how the species under study perceives conspecifics, and, hence, which features are needed for... Read More about Perception of artificial conspecifics by bearded dragons (Pogona vitticeps).

Lateralized Eye Use Towards Video Stimuli in Bearded Dragons (Pogona vitticeps) (2017)
Journal Article
Frohnwieser, A., Pike, T., Murray, J., & Wilkinson, A. (2017). Lateralized Eye Use Towards Video Stimuli in Bearded Dragons (Pogona vitticeps). Animal behavior and cognition, 4(3), 340-348. https://doi.org/10.26451/abc.04.03.11.2017

Lateralized eye use is thought to increase brain efficiency, as the two hemispheres process different information perceived by the eyes. It has been observed in a wide variety of vertebrate species and, in general, information about conspecifics appe... Read More about Lateralized Eye Use Towards Video Stimuli in Bearded Dragons (Pogona vitticeps).

Can cognitive biases in robots make more "likeable" human-robot interactions than the robots without such biases : case studies using five biases on humanoid robot (2016)
Journal Article
Biswas, M., & Murray, J. (2016). Can cognitive biases in robots make more "likeable" human-robot interactions than the robots without such biases : case studies using five biases on humanoid robot. International journal of artificial life research, 6(1), 1-29. https://doi.org/10.4018/ijalr.2016010101

The research presented in the paper aims to develop long-term companionship between cognitively imperfect robots and humans. In order to develop cognitively imperfect robot, the research suggests to implement various cognitive biases in a robot's int... Read More about Can cognitive biases in robots make more "likeable" human-robot interactions than the robots without such biases : case studies using five biases on humanoid robot.

The effects of cognitive biases and imperfectness in long-term robot-human interactions: Case studies using five cognitive biases on three robots (2016)
Journal Article
Biswas, M., & Murray, J. (2017). The effects of cognitive biases and imperfectness in long-term robot-human interactions: Case studies using five cognitive biases on three robots. Cognitive systems research, 43, 266-290. https://doi.org/10.1016/j.cogsys.2016.07.007

© 2016 Elsevier B.V. The research presented in this paper demonstrates a model for aiding human-robot companionship based on the principle of ‘human’ cognitive biases applied to a robot. The aim of this work was to study how cognitive biases can affe... Read More about The effects of cognitive biases and imperfectness in long-term robot-human interactions: Case studies using five cognitive biases on three robots.

Using robots to understand animal cognition (2016)
Journal Article
Frohnwieser, A., Murray, J. C., Pike, T. W., & Wilkinson, A. (2016). Using robots to understand animal cognition. Journal of the Experimental Analysis of Behavior, 105(1), 14-22. https://doi.org/10.1002/jeab.193

In recent years, robotic animals and humans have been used to answer a variety of questions related to behavior. In the case of animal behavior, these efforts have largely been in the field of behavioral ecology. They have proved to be a useful tool... Read More about Using robots to understand animal cognition.

Automatic classification of flying bird species using computer vision techniques (2015)
Journal Article
Atanbori, J., Duan, W., Murray, J., Appiah, K., & Dickinson, P. (2016). Automatic classification of flying bird species using computer vision techniques. Pattern recognition letters, 81, 53-62. https://doi.org/10.1016/j.patrec.2015.08.015

Bird populations are identified as important biodiversity indicators, so collecting reliable population data is important to ecologists and scientists. However, existing manual monitoring methods are labour-intensive, time-consuming, and potentially... Read More about Automatic classification of flying bird species using computer vision techniques.

Colias: An autonomous micro robot for swarm robotic applications (2014)
Journal Article
Arvin, F., Murray, J., Zhang, C., & Yue, S. (2014). Colias: An autonomous micro robot for swarm robotic applications. International journal of advanced robotic systems, 11(1), 113. https://doi.org/10.5772/58730

Robotic swarms that take inspiration from nature are becoming a fascinating topic for multi-robot researchers. The aim is to control a large number of simple robots in order to solve common complex tasks. Due to the hardware complexities and cost of... Read More about Colias: An autonomous micro robot for swarm robotic applications.

Development and deployment of an intelligent kite aerial photography platform (iKAPP) for site surveying and image acquisition (2013)
Journal Article
Murray, J. C., Neal, M. J., & Labrosse, F. (2013). Development and deployment of an intelligent kite aerial photography platform (iKAPP) for site surveying and image acquisition. Journal of field robotics, 30(2), 288-307. https://doi.org/10.1002/rob.21448

Aerial photographs and images are used by a variety of industries, including farming, landscaping, surveying, and agriculture, as well as academic researchers including archaeologists and geologists. Aerial imagery can provide a valuable resource for... Read More about Development and deployment of an intelligent kite aerial photography platform (iKAPP) for site surveying and image acquisition.

Robotic sound-source localisation architecture using cross-correlation and recurrent neural networks (2009)
Journal Article
Murray, J. C., Erwin, H. R., & Wermter, S. (2009). Robotic sound-source localisation architecture using cross-correlation and recurrent neural networks. Neural Networks, 22(2), 173-189. https://doi.org/10.1016/j.neunet.2009.01.013

In this paper we present a sound-source model for localising and tracking an acoustic source of interest along the azimuth plane in acoustically cluttered environments, for a mobile service robot. The model we present is a hybrid architecture using c... Read More about Robotic sound-source localisation architecture using cross-correlation and recurrent neural networks.

A computer vision approach to classification of birds in flight from video sequences
Presentation / Conference Contribution
Atanbori, J., Duan, W., Murray, J., Appiah, K., & Dickinson, P. (2015, September). A computer vision approach to classification of birds in flight from video sequences. Presented at Machine Vision of Animals and their Behaviour Workshop 2015, Swansea, UK

Bird populations are an important bio-indicator, ; so collecting reliable data is useful for ecologists helping conserve and manage fragile ecosystems. However, existing manual monitoring methods are labour-intensive, time-consuming, and error-prone.... Read More about A computer vision approach to classification of birds in flight from video sequences.

Using robots to understand animal social cognition
Presentation / Conference Contribution
Frohnwieser, A., Murray, J., Pike, T., & Wilkinson, A. (2015, March). Using robots to understand animal social cognition. Presented at ASAB Easter Conference 2015, Durham, UK

In recent years, robotic animals and humans have been used to answer a variety of questions related to behavior. In the case of animal behavior, these efforts have largely been in the field of behavioral ecology. They have proved to be a useful tool... Read More about Using robots to understand animal social cognition.

A recurrent neural network for sound-source motion tracking and prediction
Presentation / Conference Contribution
Murray, J. C., Erwin, H., & Wermter, S. (2004, July). A recurrent neural network for sound-source motion tracking and prediction. Presented at Proceedings of the International Joint Conference on Neural Networks, Montreal, Que., Canada

Recurrent neural networks (RNN) have been used in many applications for both pattern detection and prediction. This paper shows the use of RNN's as a speed classifier and predictor for a robotic sound source tracking system. The system requires exten... Read More about A recurrent neural network for sound-source motion tracking and prediction.