A High-Force Gripper with Embedded Multimodal Sensing for Powerful and Perception Driven Grasping

TL;DR

The paper tackles the gap in robotic grasping by delivering a modular end-effector that combines high grasping force with embedded multimodal sensing for perception-driven control. It employs a series elastic actuator capable of up to 16.5 Nm torque to achieve 110 N at 0.15 m, while integrating an eye-in-hand camera, ToF, IMU, and microphone to enable autonomous perception-driven grasping. It introduces dynamic-motion and thermal-state payload metrics to thoroughly evaluate performance under robot motion and heating, and demonstrates perception-guided grasping on the CENTAURO robot with a YOLOv8-based perception pipeline and offline speech recognition. The work advances practical, robust manipulation by enabling on-board sensing, high-strength grasping, and autonomous interaction, with clear pathways for future pose estimation enhancements and softer, more adaptable jaw designs.

Abstract

Modern humanoid robots have shown their promising potential for executing various tasks involving the grasping and manipulation of objects using their end-effectors. Nevertheless, in the most of the cases, the grasping and manipulation actions involve low to moderate payload and interaction forces. This is due to limitations often presented by the end-effectors, which can not match their arm-reachable payload, and hence limit the payload that can be grasped and manipulated. In addition, grippers usually do not embed adequate perception in their hardware, and grasping actions are mainly driven by perception sensors installed in the rest of the robot body, frequently affected by occlusions due to the arm motions during the execution of the grasping and manipulation tasks. To address the above, we developed a modular high grasping force gripper equipped with embedded multi-modal perception functionalities. The proposed gripper can generate a grasping force of 110 N in a compact implementation. The high grasping force capability is combined with embedded multi-modal sensing, which includes an eye-in-hand camera, a Time-of-Flight (ToF) distance sensor, an Inertial Measurement Unit (IMU) and an omnidirectional microphone, permitting the implementation of perception-driven grasping functionalities. We extensively evaluated the grasping force capacity of the gripper by introducing novel payload evaluation metrics that are a function of the robot arm's dynamic motion and gripper thermal states. We also evaluated the embedded multi-modal sensing by performing perception-guided enhanced grasping operations.

Figures (15)

• Figure 1: The developed gripper mounted on the arm of the CENTAURO robot.
• Figure 2: The CAD design of the gripper, highlighting its core modules.
• Figure 3: The gripper's actuator with its driver electronics.
• Figure 4: Different types of jaw modules, on the left general jaw modules, in the middle jaw modules dedicated to the grasping of planar formwork elements, and, on the right, jaw modules shaped to provide enhanced grasping of large cylindrical objects.
• Figure 5: The add-on multi-modal sensing unit indicating indicating the principal sensors. The unit incorporates also a 6-axis IMU sensor.