Maggie B. Wigness — accepted AI-conference papers

2025

Coordinated Multi-Robot Navigation with Formation Adaptation

Zihao Deng, Peng Gao, Williard Joshua Jose, Christopher M. Reardon, Maggie B. Wigness, John G. Rogers +1

ICRA 2025

Coordinated multi-robot navigation is an essential ability for a team of robots operating in diverse environments. Robot teams often need to maintain specific formations, such as wedge formations, to enhance visibility, positioning, and efficiency during fast movement. However, complex environments

Cited by 4 Source ↗Scholar ↗

2025

M2P2: A Multi-Modal Passive Perception Dataset for Off-Road Mobility in Extreme Low-Light Conditions

Aniket Datar, Anuj Pokhrel, Mohammad Nazeri, Madhan B. Rao, Harsh Rangwala, Chenhui Pan +6

IROS 2025

Long-duration, off-road, autonomous missions require robots to continuously perceive their surroundings regardless of the ambient lighting conditions. Most existing autonomy systems heavily rely on active sensing, e.g., LiDAR, RADAR, and Time-of-Flight sensors, or use (stereo) visible light imaging

Cited by 6 Source ↗Scholar ↗

2025

Self-Reflective Perceptual Adaptation for Robust Ground Navigation in Unstructured Off-Road Environments

Sriram Siva, Oscar Youngquist, Maggie B. Wigness, John G. Rogers, Hao Zhang

ICRA 2025

Autonomous ground robots navigating unstructured off-road environments face perceptual challenges, such as sensor obscuration or failure, which can lead to inaccurate perception or navigation failures. While robot adaptation has recently gained increasing attention, self-reflective robot adaptation,

Cited by 0 Source ↗Scholar ↗