We present a map-less path planning algorithm based on Deep Reinforcement Learning (DRL) for mobi... more We present a map-less path planning algorithm based on Deep Reinforcement Learning (DRL) for mobile robots navigating in unknown environment that only relies on 40-dimensional raw laser data and odometry information. The planner is trained using a reward function shaped based on the online knowledge of the map of the training environment, obtained using grid-based Rao-Blackwellized particle filter, in an attempt to enhance the obstacle awareness of the agent. The agent is trained in a complex simulated environment and evaluated in two unseen ones. We show that the policy trained using the introduced reward function not only outperforms standard reward functions in terms of convergence speed, by a reduction of 36.9\% of the iteration steps, and reduction of the collision samples, but it also drastically improves the behaviour of the agent in unseen environments, respectively by 23\% in a simpler workspace and by 45\% in a more clustered one. Furthermore, the policy trained in the sim...
At vital moments in professional soccer matches, penalties were often missed. Psychological facto... more At vital moments in professional soccer matches, penalties were often missed. Psychological factors, such as anxiety and pressure, are among the critical causes of the mistakes, commonly known aschoking under pressure. Nevertheless, the factors have not been fully explored. In this study, we used functional near-infrared spectroscopy (fNIRS) to investigate the influence of the brain on this process. Anin-situstudy was set-up (N= 22), in which each participant took 15 penalties under three different pressure conditions: without a goalkeeper, with an amiable goalkeeper, and with a competitive goalkeeper. Both experienced and inexperienced soccer players were recruited, and the brain activation was compared across groups. Besides, fNIRS activation was compared between sessions that participants felt anxious against sessions without anxiety report, and between penalty-scoring and -missing sessions. The results show that the task-relevant brain region, the motor cortex, was more activate...
Proceedings of the 2015 ACM on International Conference on Multimodal Interaction, 2015
Advances in the field of touch recognition could open up applications for touch-based interaction... more Advances in the field of touch recognition could open up applications for touch-based interaction in areas such as Human-Robot Interaction (HRI). We extended this challenge to the research community working on multimodal interaction with the goal of sparking interest in the touch modality and to promote exploration of the use of data processing techniques from other more mature modalities for touch recognition. Two data sets were made available containing labeled pressure sensor data of social touch gestures that were performed by touching a touch-sensitive surface with the hand. Each set was collected from similar sensor grids, but under conditions reflecting different application orientations: CoST: Corpus of Social Touch and HAART: The Human-Animal Affective Robot Touch gesture set. In this paper we describe the challenge protocol and summarize the results from the touch challenge hosted in conjunction with the 2015 ACM International Conference on Multimodal Interaction (ICMI). The most important outcomes of the challenges were: (1) transferring techniques from other modalities, such as image processing, speech, and human action recognition provided valuable feature sets; (2) gesture classification confusions were similar despite the various data processing methods used.
Automatically recovering human poses from visual input is useful but challenging due to variation... more Automatically recovering human poses from visual input is useful but challenging due to variations in image space and the high dimensionality of the pose space. In this paper, we assume that a human silhouette can be extracted from monocular visual input. We compare three shape descriptors that are used in the encoding of silhouettes: Fourier descriptors, shape contexts and Hu moments. An examplebased approach is taken to recover upper body poses from these descriptors. We perform experiments with deformed silhouettes to test each descriptor’s robustness against variations in body dimensions, viewpoint and noise. It is shown that Fourier descriptors and shape context histograms outperform Hu moments for all deformations. 1
The main objective of this roadmap is to provide a global perspective on the BCI field now and in... more The main objective of this roadmap is to provide a global perspective on the BCI field now and in the future. For readers not familiar with BCIs, we introduce basic terminology and concepts. We discuss what BCIs are, what BCIs can do, and who can benefit from BCIs. We illustrate our arguments with use cases to support the main messages. After reading this roadmap you will have a clear picture of the potential benefits and challenges of BCIs, the steps necessary to bridge the gap between current and future applications, and the potential impact of BCIs on society in the next decade and beyond.
We present a map-less path planning algorithm based on Deep Reinforcement Learning (DRL) for mobi... more We present a map-less path planning algorithm based on Deep Reinforcement Learning (DRL) for mobile robots navigating in unknown environment that only relies on 40-dimensional raw laser data and odometry information. The planner is trained using a reward function shaped based on the online knowledge of the map of the training environment, obtained using grid-based Rao-Blackwellized particle filter, in an attempt to enhance the obstacle awareness of the agent. The agent is trained in a complex simulated environment and evaluated in two unseen ones. We show that the policy trained using the introduced reward function not only outperforms standard reward functions in terms of convergence speed, by a reduction of 36.9\% of the iteration steps, and reduction of the collision samples, but it also drastically improves the behaviour of the agent in unseen environments, respectively by 23\% in a simpler workspace and by 45\% in a more clustered one. Furthermore, the policy trained in the sim...
At vital moments in professional soccer matches, penalties were often missed. Psychological facto... more At vital moments in professional soccer matches, penalties were often missed. Psychological factors, such as anxiety and pressure, are among the critical causes of the mistakes, commonly known aschoking under pressure. Nevertheless, the factors have not been fully explored. In this study, we used functional near-infrared spectroscopy (fNIRS) to investigate the influence of the brain on this process. Anin-situstudy was set-up (N= 22), in which each participant took 15 penalties under three different pressure conditions: without a goalkeeper, with an amiable goalkeeper, and with a competitive goalkeeper. Both experienced and inexperienced soccer players were recruited, and the brain activation was compared across groups. Besides, fNIRS activation was compared between sessions that participants felt anxious against sessions without anxiety report, and between penalty-scoring and -missing sessions. The results show that the task-relevant brain region, the motor cortex, was more activate...
Proceedings of the 2015 ACM on International Conference on Multimodal Interaction, 2015
Advances in the field of touch recognition could open up applications for touch-based interaction... more Advances in the field of touch recognition could open up applications for touch-based interaction in areas such as Human-Robot Interaction (HRI). We extended this challenge to the research community working on multimodal interaction with the goal of sparking interest in the touch modality and to promote exploration of the use of data processing techniques from other more mature modalities for touch recognition. Two data sets were made available containing labeled pressure sensor data of social touch gestures that were performed by touching a touch-sensitive surface with the hand. Each set was collected from similar sensor grids, but under conditions reflecting different application orientations: CoST: Corpus of Social Touch and HAART: The Human-Animal Affective Robot Touch gesture set. In this paper we describe the challenge protocol and summarize the results from the touch challenge hosted in conjunction with the 2015 ACM International Conference on Multimodal Interaction (ICMI). The most important outcomes of the challenges were: (1) transferring techniques from other modalities, such as image processing, speech, and human action recognition provided valuable feature sets; (2) gesture classification confusions were similar despite the various data processing methods used.
Automatically recovering human poses from visual input is useful but challenging due to variation... more Automatically recovering human poses from visual input is useful but challenging due to variations in image space and the high dimensionality of the pose space. In this paper, we assume that a human silhouette can be extracted from monocular visual input. We compare three shape descriptors that are used in the encoding of silhouettes: Fourier descriptors, shape contexts and Hu moments. An examplebased approach is taken to recover upper body poses from these descriptors. We perform experiments with deformed silhouettes to test each descriptor’s robustness against variations in body dimensions, viewpoint and noise. It is shown that Fourier descriptors and shape context histograms outperform Hu moments for all deformations. 1
The main objective of this roadmap is to provide a global perspective on the BCI field now and in... more The main objective of this roadmap is to provide a global perspective on the BCI field now and in the future. For readers not familiar with BCIs, we introduce basic terminology and concepts. We discuss what BCIs are, what BCIs can do, and who can benefit from BCIs. We illustrate our arguments with use cases to support the main messages. After reading this roadmap you will have a clear picture of the potential benefits and challenges of BCIs, the steps necessary to bridge the gap between current and future applications, and the potential impact of BCIs on society in the next decade and beyond.
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