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There have been a number of corner detection methods proposed for event cameras in the last years, since event-driven computer vision has become more accessible. Current state-of-the-art have either unsatisfactory accuracy or real-time performance when considered for practical use, for example when a camera is randomly moved in an unconstrained environment. In this paper, we present yet another method to perform corner detection, dubbed look-up event-Harris (luvHarris), that employs the Harris algorithm for high accuracy but manages an improved event throughput. Our method has two major contributions, 1. a novel “threshold ordinal event-surface” that removes certain tuning parameters and is well suited for Harris operations, and 2. an implementation of the Harris algorithm such that the computational load per event is minimised and computational heavy convolutions are performed only ‘as-fast-as-possible’, i.e., only as computational resources are available. The result is a practical, real-time, and robust corner detector that runs more than $2.6\times$ 2. 6 × the speed of current state-of-the-art; a necessity when using a high-resolution event-camera in real-time. We explain the considerations taken for the approach, compare the algorithm to current state-of-the-art in terms of computational performance and detection accuracy, and discuss the validity of the proposed approach for event cameras. [ABSTRACT FROM AUTHOR]

Despite extensive studies on cyclic tasks in robotics, definitive solutions for the problem of trajectory generation for periodic motions have not been achieved so far. In this paper, we present an approach for online trajectory generation from a library of desired periodic trajectories. The proposed approach consists of a Central Pattern Generator (CPG) architecture ensuring entrainment of any periodic trajectory, smooth motion modulation and observing position and velocity limits of the robot. The proposed CPG is composed of a synchronized network of novel bounded output oscillatory systems. Every oscillatory system is a three-dimensional dynamical system encoding a one-dimensional periodic function as a stable limit cycle. We also use the state transformation method to bound the oscillator's output and its first time derivative. Finally, we present a synchronization technique to construct a synchronized network of the proposed oscillators for generating multi dimensional periodic functions. Using Lyapunov based arguments, we prove that the proposed CPG ensures stability, convergence, and synchronization of the desired trajectory. The soundness of the proposed oscillator and the resulting CPG are validated both in simulations and experiments on the humanoid robot iCub. • Designing a programmable oscillator with a desired limit cycle. • Comparing the concept of trajectory tracking and limit cycle tracking in robotics. • Designing a central pattern generator for online trajectory generation from a library of the desired periodic trajectories. • Considering position and velocity joint limits of the robot in central pattern generator architecture. [ABSTRACT FROM AUTHOR]