Max Robotics — Global Service Robot Directory + US Certification

About

Orion Taylor is a leading roboticist whose research focuses on enabling robots to autonomously grasp and manipulate objects in unstructured, cluttered environments—a critical challenge for real-world applications like warehouse automation and domestic assistance. His most influential work, the multi-award-winning "Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching," has garnered over 700 citations across its versions. This system broke new ground by allowing robots to handle a wide range of unknown objects without task-specific training data, combining multi-affordance grasping with cross-domain image matching for robust recognition. Taylor also played a key role in Team MIT’s entry to the Amazon Picking Challenge, a landmark competition that pushed the boundaries of warehouse automation. More recently, he has advanced the theory of contact configuration regulation, enabling robots to manipulate unknown objects by controlling the location and mode of all contacts between the robot, object, and environment. His work on intermittent and multiple contacts represents a significant step toward more dexterous, adaptive robotic manipulation. Taylor’s research is essential reading for anyone interested in the intersection of perception, control, and autonomous grasping.