Generating Whole-Body Avoidance Motion through Localized Proximity Sensing

TL;DR

This paper introduces a control algorithm for robotic manipulators that uses localized proximity sensing and geometric fusion to generate whole-body avoidance motions, enabling safe human-robot interaction in unstructured environments.

Contribution

It presents a novel hierarchical control approach that fuses multi-zone ToF sensor data with geometric models to enable avoidance motions of both sensorized and non-sensorized robot links.

Findings

Achieves up to 100 mm improvement in distance margin.

Demonstrates effective avoidance in static and dynamic scenarios.

Performs comparably to existing sensor placement strategies.

Abstract

This paper presents a novel control algorithm for robotic manipulators in unstructured environments using proximity sensors partially distributed on the platform. The proposed approach exploits arrays of multi zone Time-of-Flight (ToF) sensors to generate a sparse point cloud representation of the robot surroundings. By employing computational geometry techniques, we fuse the knowledge of robot geometric model with ToFs sensory feedback to generate whole-body motion tasks, allowing to move both sensorized and non-sensorized links in response to unpredictable events such as human motion. In particular, the proposed algorithm computes the pair of closest points between the environment cloud and the robot links, generating a dynamic avoidance motion that is implemented as the highest priority task in a two-level hierarchical architecture. Such a design choice allows the robot to work safely alongside humans even without a complete sensorization over the whole surface. Experimental validation demonstrates the algorithm effectiveness both in static and dynamic scenarios, achieving comparable performances with respect to well established control techniques that aim to move the sensors mounting positions on the robot body. The presented algorithm exploits any arbitrary point on the robot surface to perform avoidance motion, showing improvements in the distance margin up to 100 mm, due to the rendering of virtual avoidance tasks on non-sensorized links.