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cs.RO2026

UGV-Conditioned Multi-UAV Informative Planning on a Shared Exposure Belief

Lars Oerlemans, Moji Shi, Marija Popovic

Safe ground navigation in large, threat-augmented environments requires aerial support that actively reduces the risks that a ground vehicle faces along its route. Existing aerial…

cs.RO2026

Perception-Aware Autonomous Exploration in Feature-Limited Environments

Moji Shi, Rajitha de Silva, Hang Yu +3

Autonomous exploration in unknown environments typically relies on onboard state estimation for localisation and mapping. Existing exploration methods primarily maximise coverage e…

cs.RO2026

EAAE: Energy-Aware Autonomous Exploration for UAVs in Unknown 3D Environments

Jacob Elskamp, Moji Shi, Leonard Bauersfeld +2

Battery-powered multirotor unmanned aerial vehicles (UAVs) can rapidly map unknown environments, but mission performance is often limited by energy rather than geometry alone. Stan…

cs.RO2024

Learning Humanoid Locomotion with Perceptive Internal Model

Junfeng Long, Junli Ren, Moji Shi +4

In contrast to quadruped robots that can navigate diverse terrains using a "blind" policy, humanoid robots require accurate perception for stable locomotion due to their high degre…

cs.RO2024

Decentralized Multi-Agent Trajectory Planning in Dynamic Environments with Spatiotemporal Occupancy Grid Maps

Siyuan Wu, Gang Chen, Moji Shi +1

This paper proposes a decentralized trajectory planning framework for the collision avoidance problem of multiple micro aerial vehicles (MAVs) in environments with static and dynam…

cs.RO2024

Evaluating Dynamic Environment Difficulty for Obstacle Avoidance Benchmarking

Moji Shi, Gang Chen, Álvaro Serra Gómez +2

Dynamic obstacle avoidance is a popular research topic for autonomous systems, such as micro aerial vehicles and service robots. Accurately evaluating the performance of dynamic ob…