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About

Dominik Kaserer is a leading researcher in robotic manipulation, with a particular focus on time-optimal motion planning and cooperative grasping. His work addresses the complex challenge of enabling robots to manipulate objects that are loosely placed—rather than rigidly grasped—a scenario he terms the "general waiter problem." Kaserer's major contributions include developing consistent methods for time-optimal path following and admittance control, notably achieving sensorless force control for redundant industrial manipulators. His most cited paper, "Time Optimal Motion Planning and Admittance Control for Cooperative Grasping" (2020, 34 citations), establishes foundational techniques for multi-robot systems handling objects through unilateral contact. Further impactful works include "Time-optimal robotic manipulation on a predefined path of loosely placed objects" (2022, 26 citations) and "Admittance control of a redundant industrial manipulator without using force/torque sensors" (2016, 9 citations). Kaserer has also contributed to automated 3D scanning through depth sensor-based object detection and path planning, and developed novel methods for geometric robot calibration using laser pointers and cameras. His research, spanning online synchronization with geometric constraints and velocity/jerk limits, has accumulated over 90 citations, demonstrating significant influence in advancing robotic dexterity and efficiency for real-world manipulation tasks.