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20172025
most citedToward Safety-Aware Informative Motion Planning for Legged Robots

22 citations · 44 across the 6 of their papers we have counts for

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14 papers · 1 filter

cs.RO2025

Standing Tall: Sim to Real Fall Classification and Lead Time Prediction for Bipedal Robots

Gokul Prabhakaran, Jessy W. Grizzle, M. Eva Mungai

This paper extends a previously proposed fall prediction algorithm to a real-time (online) setting, with implementations in both hardware and simulation. The system is validated on…

cs.RO20228 cited

Informable Multi-Objective and Multi-Directional RRT* System for Robot Path Planning

Jiunn-Kai Huang, Yingwen Tan, Dongmyeong Lee +2

Multi-objective or multi-destination path planning is crucial for mobile robotics applications such as mobility as a service, robotics inspection, and electric vehicle charging for…

cs.RO202122 cited

Toward Safety-Aware Informative Motion Planning for Legged Robots

Sangli Teng, Yukai Gong, Jessy W. Grizzle +1

This paper reports on developing an integrated framework for safety-aware informative motion planning suitable for legged robots. The information-gathering planner takes a dense st…

cs.RO2020

Global Unifying Intrinsic Calibration for Spinning and Solid-State LiDARs

Jiunn-Kai Huang, Chenxi Feng, Madhav Achar +2

Sensor calibration, which can be intrinsic or extrinsic, is an essential step to achieve the measurement accuracy required for modern perception and navigation systems deployed on…

cs.RO2019

Improvements to Target-Based 3D LiDAR to Camera Calibration

Jiunn-Kai Huang, Jessy W. Grizzle

The homogeneous transformation between a LiDAR and monocular camera is required for sensor fusion tasks, such as SLAM. While determining such a transformation is not considered gla…

cs.RO20195 cited

Adaptive Continuous Visual Odometry from RGB-D Images

Tzu-Yuan Lin, William Clark, Ryan M. Eustice +3

In this paper, we extend the recently developed continuous visual odometry framework for RGB-D cameras to an adaptive framework via online hyperparameter learning. We focus on the…