Learning-based methods, such as imitation learning (IL) and reinforcement learning (RL), can produce excel control policies over challenging agile robot tasks, such as sports robot. However, no existing work has harmo...
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This paper presents the Motion and Vision Sensing Integration-based Agile Badminton Robot (MV-BMR), a real-time system that plays badminton with human players. Current badminton robots excel at handling low-speed stri...
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Recently, intelligent sports analytics is becoming a hot area in both industry and academia for coaching, practicing tactic and technical analysis. With the growing trend of bringing sports analytics to live broadcast...
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ISBN:
(纸本)9781538641293
Recently, intelligent sports analytics is becoming a hot area in both industry and academia for coaching, practicing tactic and technical analysis. With the growing trend of bringing sports analytics to live broadcasting, sports robots and common playfield, a low cost system that is easy to deploy and performs real-time and accurate sports analytics is very desirable. However, existing systems, such as Hawk-Eye, cannot satisfy these requirements due to various factors. In this paper, we present MV-Sports, a cost-effective system for real-time sports analysis based on motion and vision sensor integration. Taking tennis as a case study, we aim to recognize player shot types and measure ball states. For fine-grained player action recognition, we leverage motion signal for fast action highlighting and propose a long short term memory (LSTM)-based framework to integrate MV data for training and classification. For ball state measurement, we compute the initial ball state via motion sensing and devise an extended kalman filter (EKF)-based approach to combine ball motion physics-based tracking and vision positioning-based tracking to get more accurate ball state. We implement MV-Sports on commercial off-the-shelf (COTS) devices and conduct real-world experiments to evaluate the performance of our system. The results show our approach can achieve accurate player action recognition and ball state measurement with sub-second latency.
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