Ashley Kleinhans

Council for Scientific and Industrial Research

Papers

Total Citations

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About

Ashley Kleinhans is a pioneering researcher at the intersection of neuromorphic robotics and computational neuroscience, whose work focuses on bridging biological principles with robotic systems. Her most influential contribution, "Serendipitous Offline Learning in a Neuromorphic Robot" (2016, 36 citations), introduces a hybrid learning paradigm where a mobile robot, equipped with a spike-based silicon retina, evolves complex sensorimotor mappings from a minimal set of hard-coded reflexes. This work demonstrates how neuromorphic hardware can achieve adaptive behavior through serendipitous offline learning, offering a scalable approach to autonomous robotics. Kleinhans also contributed to the field of robotic grasping with "G3DB: A Database of Successful and Failed Grasps" (2015, 7 citations), a resource that provides RGB-D images, point clouds, and mesh models to benchmark grasp planning algorithms. Additionally, her modeling of shape hierarchy for visually guided grasping (2014, 4 citations) draws inspiration from monkey anterior intraparietal area (AIP) neurons, linking curvature and gradient processing to hand shaping. Her work has been presented at major venues like IEEE ICRA, showcasing her impact on biologically inspired robotics and sensorimotor learning.