Best of ICRA - July 20, 2026

The Best of ICRA is a three-day virtual meetup series featuring researchers presenting their accepted papers from the 2026 International Conference on Robotics and Automation (ICRA).

Each session features a curated lineup of speakers sharing cutting-edge research across robotics, computer vision, and AI — straight from papers accepted at one of the field's top conferences.

Whether you're a researcher, engineer, or practitioner, you'll leave with a sharper view of where the field is heading.

Accurate sensing and mapping are critical for autonomous underwater vehicles operating in obstacle-rich environments. While vision provides high-resolution data, it fails in turbid water, and whereas sonar is robust to turbidity, it suffers from low resolution and elevation ambiguity.

To overcome these limitations, our recent work introduces an opti-acoustic sensor fusion framework that pairs a monocular camera with a stereo sonar to resolve elevation ambiguity and produce fully defined 3D point clouds. These multi-modal points are then fused using a confidence-weighted Gaussian Process Volumetric Mapping framework that prioritizes high-confidence, safety-critical data.

Ultimately, field trials and experimental results validate that this framework successfully captures complex geometries to ensure reliable navigation under degraded sensing conditions.

Autonomous inspection of industrial environments requires robots to identify and prioritize specific objects of interest, rather than exhaustively exploring their surroundings. This talk presents a deep reinforcement learning framework which enables aerial robots to simultaneously locate, visually inspect semantic targets, and navigate collision-free in unknown environments using only onboard sensors.

The policy generalizes from training on primitive shapes to inspecting complex, real-world structures in real-world settings. The talk also covers a second line of work on active perception, where the the flying agent learns to actively steer its camera sensor during navigation to maximize situational awareness.

Together, these approaches push toward truly autonomous robots that understand not just where to go, but what to look at.

This work investigates whether a socially supportive virtual robot can enhance children's self-esteem and social engagement through game-based interactions. We conducted a month-long study with 23 children in India, where participants played a video game with or without a virtual robot that provided positive reinforcement.

Our results showed that children interacting with the robot demonstrated significant improvements in global self-esteem, friendship quality and quantity, and sustained motivation and enjoyment. These findings highlight the potential of socially supportive virtual robots as tools for promoting children's psychological well-being and social development.