Video Friday: Meet Microduck
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.Humanoids Summit Seoul: 22–23 September 2026, SEOULIROS 2026: 27 September–1 October 2026, PITTSBURGHCoRL 2026: 9–12 November…
AI Companion Robots Are Closing the Human Connection in Modern Homes
This article is brought to you by Ollobot.From about 2017, individuals began to truly connect with the initial wave of companion robots. These devices had personality, moved around, joked, and answered when you spoke to them. Most early companion robots, however, were still limited by simple voice-command interactions and narrow functionality. Once the novelty wore…
LEGO: Learning and Executing Generalized Operational Skill Chains for Autonomous Condition-Adaptive Surgical Knot-Tying From Few-Shot Demonstrations
Autonomous robotic knot-tying is a pivotal yet challenging task in minimally invasive surgery. However, reliable deployment remains difficult due to the need for rapid adaptation to diverse surgical scenarios. Off-the-shelf approaches struggle to handle interactions between flexible sutures and rigid instruments, which often require extensive training data, failing to generalize across varying conditions. In this…
An Equivariant Filter-Based State Estimator for Tightly-Coupled LiDAR–Radar–Inertial Odometry
Over the past decade, the fusion of light detection and ranging (LiDAR) and inertial navigation systems (INS) has become a reliable solution for environmental perception in intelligent mobile platforms. However, LiDAR performance degrades under adverse weather conditions. Millimeter-wave radar offers complementary benefits: it is robust to environmental disturbances and provides direct Doppler velocity measurements. Moreover,…
A Meta-Learning-Based Adaptive Hybrid Evolutionary Algorithm for Dynamic Resource Configuration in Regional Industrial Cluster
Dynamic resource configuration in regional industrial clusters is pivotal for unlocking their collective efficiency and ensuring resilience in cyber-physical production systems. However, static optimization methods suffer from a fundamental mismatch against volatile industrial rhythms, lacking the situational awareness to adapt strategies, the structural diversity to prevent stagnation, and the precision required for operational execution. To…
Multimodal Perception for Underwater Hitchhiking of Robotic Remora: Integrating Semantic Vision and ToF Sensing
Hitchhiking is a low-energy locomotion strategy employed by remoras. Its success critically depends on the ability to accurately perceive and identify suitable attachment targets throughout both the far-field approach and near-field contact stages. Motivated by this biological insight, this work focuses on enhancing perception for hitchhiking tasks and proposes a multimodal perception framework for a…
CLEAR: A Semantic–Geometric Terrain Abstraction for Large-Scale Unstructured Environments
Long-horizon navigation in unstructured environments demands terrain abstractions that scale to tens of square kilometers while preserving semantic and geometric structure. Grids scale poorly and quadtrees misalign with terrain boundaries. Neither encodes terrain semantics essential for traversability-aware planning, yielding infeasible or inefficient paths for autonomous ground vehicles operating over 10+ km$^{2}$. CLEAR (Connected Landcover Elevation…
Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation
The LiDAR 3D object detector that strikes a balance between accuracy and speed is crucial for achieving real-time perception in autonomous driving. However, many existing LiDAR detection models depend on complex feature transformations, leading to poor real-time performance and high resource consumption, which limits their practical effectiveness. In this work, we propose a Faster LiDAR…
EllipseLIO: Adaptive LiDAR Inertial Odometry With an Ellipsoid Representation
LiDAR Inertial Odometry (LIO) is a critical component for many mobile robots that need to navigate without relying on external positioning (e.g., GPS). Platforms that operate autonomously in different environments and with heterogeneous LiDAR sensors require a LIO approach that can adapt to these different scenarios without human intervention. Existing LIO approaches can typically provide…
Human-Led Decentralized Constant-Spacing Robot Platoons Without Communication
Leader-follower-type platooning can aid human management of multiple robots through complex environments, where the human manages constraints and obstacle-avoidance of the lead robot and the other robots follow the same human-generated leader trajectory. However, the spacing error between robots in the platoon should be small to ensure that each robot in the platoon maintains visual…