activity
20222025
most citedA Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approaches

51 citations · 52 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2025

Safe Gap-based Planning in Dynamic Settings

Max Asselmeier, Abdel Zaro, Dhruv Ahuja +2

This chapter extends the family of perception-informed gap-based local planners to dynamic environments. Existing perception-informed local planners that operate in dynamic environ…

cs.RO2025

QuadPiPS: A Perception-informed Footstep Planner for Quadrupeds With Semantic Affordance Prediction

Max Asselmeier, Ye Zhao, Patricio A. Vela

This work proposes QuadPiPS, a perception-informed framework for quadrupedal foothold planning in the perception space. QuadPiPS employs a novel ego-centric local environment repre…

cs.RO2024★ 51 cited

A Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approaches

Zhigen Zhao, Shuo Cheng, Yan Ding +4

Task and Motion Planning (TAMP) integrates high-level task planning and low-level motion planning to equip robots with the autonomy to effectively reason over long-horizon, dynamic…

cs.RO2023★ 1 cited

Hierarchical Experience-informed Navigation for Multi-modal Quadrupedal Rebar Grid Traversal

Max Asselmeier, Jane Ivanova, Ziyi Zhou +2

This study focuses on a layered, experience-based, multi-modal contact planning framework for agile quadrupedal locomotion over a constrained rebar environment. To this end, our hi…

cs.RO2022

Dynamic Gap: Safe Gap-based Navigation in Dynamic Environments

Max Asselmeier, Dhruv Ahuja, Abdel Zaro +3

This paper extends the family of gap-based local planners to unknown dynamic environments through generating provable collision-free properties for hierarchical navigation systems.…