Enhancing Robotic Perception with Low-Cost Fast Active Vision Achieving Sub-Millimeter Accurate Marker-Based Pose Estimation

Abstract

Robust perception of the environment is a critical challenge for robots, especially those that use mobile platforms or humanoid forms to perform manipulation tasks. Active vision, leveraging strategic camera movements and adaptive imaging parameters, holds great potential for addressing critical challenges such as achieving high accuracy in precise manipulation, ensuring low latency for rapid responsiveness, and overcoming occlusions and illumination variations in dynamic environments. This paper introduces a novel, cost-effective, and easily deployable active vision system designed to enhance visual perception for robotic applications. Integrated with a novel hybrid software setup, the system utilizes ArUco markers to achieve high-accuracy, low-latency performance, boasting sub-millimeter and sub-degree accuracy at 200 Hz with a latency of less than 15 ms. Additionally, a new measurement and evaluation procedure is presented, offering benchmarking for marker-based object detection systems that for the first time includes rotation measurements as well. The benchmarking results for the proposed system indicate that achieving the desired performance levels necessitates specialized active vision measurement strategies. For instance, to ensure high positional accuracy, the system needs precise object centering, while high rotational accuracy requires accounting for lateral or rotational offsets.