Event-Based Sensors Cut Computational Load in High-Speed Robotics

Sony AI's table tennis robot Ace uses event-based vision sensors instead of conventional high-speed cameras to track balls traveling over 30 meters per second. These sensors trigger only on brightness changes, eliminating motion blur and slashing data bandwidth compared to traditional 200–1000 fps cameras. The approach maintains microsecond precision while reducing processing overhead, suggesting a practical path for sports robotics and similar time-critical applications where standard vision systems demand excessive computational resources.