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Minglong Li

16 accepted papers

2026

CABTO: Context-Aware Behavior Tree Grounding for Robot Manipulation

AAAI 2026technical

Behavior Trees (BTs) offer a powerful paradigm for designing modular and reactive robot controllers. BT planning, an emerging field, provides theoretical guarantees for the automated generation of reliable BTs. However, BT planning typically assumes that a well-designed BT system is already grounded

Cited by 0SourcePDFScholar
2026

DR$^2$Seg: Decomposed Two-Stage Rollouts for Efficient Reasoning Segmentation in Multimodal Large Language Models

ICML 2026poster

Reasoning segmentation is an emerging vision-language task that requires reasoning over intricate text queries to precisely segment objects. However, existing methods typically suffer from overthinking, generating verbose reasoning chains that interfere with object localization in multimodal large l…

Cited by 0SourceScholar
2025

Automated Exposure Mapping for Networked Interference

ICASSP 2025accepted

By characterizing interactions and influences across individuals, networked interference aims to estimate cross-individual treatment effects. For each individual, one of the central components of existing approaches is to manually design an exposure mapping from their neighboring covariates (includi…

Cited by 0SourceScholar
2025

BTPG: A Platform and Benchmark for Behavior Tree Planning in Everyday Service Robots

IJCAI 2025

Behavior Trees (BTs) are a widely used control architecture in robotics, renowned for their robustness and safety, which are especially crucial for everyday service robots. Recently, several methods have been proposed to automatically plan BTs to accomplish specific tasks. However, existing research

2025

FutureNet-LoF: Joint Trajectory Prediction and Lane Occupancy Field Prediction with Future Context Encoding

ICRA 2025

Most prior motion prediction endeavors in autonomous driving have inadequately encoded future scenarios, leading to predictions that may fail to accurately capture the diverse movements of agents (e.g., vehicles or pedestrians). To address this, we propose FutureNet, which explicitly integrates init

Cited by 9SourceScholar
2025

HBTP: Heuristic Behavior Tree Planning with Large Language Model Reasoning

ICRA 2025

Behavior Trees (BTs) are increasingly becoming a popular control structure in robotics due to their modularity, reactivity, and robustness. In terms of BT generation methods, BT planning shows promise for generating reliable BTs. However, the scalability of BT planning is often constrained by prolon

Cited by 6SourcecodeScholar
2025

MRBTP: Efficient Multi-Robot Behavior Tree Planning and Collaboration

AAAI 2025technical

Multi-robot task planning and collaboration are critical challenges in robotics. While Behavior Trees (BTs) have been established as a popular control architecture and are plannable for a single robot, the development of effective multi-robot BT planning algorithms remains challenging due to the com…

2024

Coalition Formation Game Approach for Task Allocation in Heterogeneous Multi-Robot Systems under Resource Constraints

IROS 2024poster

This paper studies a case of the multi-robot task allocation (MRTA) problem, where each unmanned aerial vehicle (UAV) is endowed with multiple but limited resources. Completing each task necessitates UAVs to combine different resources through coalition formation, which will incur various costs incl…

Cited by 0SourceScholar
2024

Integrating Intent Understanding and Optimal Behavior Planning for Behavior Tree Generation from Human Instructions

IJCAI 2024poster

Robots executing tasks following human instructions in domestic or industrial environments essentially require both adaptability and reliability. Behavior Tree (BT) emerges as an appropriate control architecture for these scenarios due to its modularity and reactivity. Existing BT generation methods…

2024

Task Allocation in Heterogeneous Multi-Robot Systems Based on Preference-Driven Hedonic Game

ICRA 2024poster

Multiple preferences between robots and tasks have been largely overlooked in previous research on Multi-Robot Task Allocation (MRTA) problems. In this paper, we propose a preference-driven approach based on hedonic game to address the task allocation problem of muti-robot systems in emergency rescu…

Cited by 1SourceScholar
2023

Evolving Physical Instinct for Morphology and Control Co-Adaption

IROS 2023poster

The capability of a robot to perform tasks depends not only on precise motion control, but also on a well-suited body morphology. Adapting both morphology and control of robots to improve their task performance has been a widely studied and long-standing issue. While the bio-inspired bi-level optimi…

Cited by 1SourceScholar
2023

Memory-based Exploration-value Evaluation Model for Visual Navigation

ICRA 2023poster

We propose a hierarchical visual navigation solution, called Memory-based Exploration-value Evaluation Model (MEEM), to improve the agent's navigation performance. MEEM employs a hierarchical policy to tackle the challenge of sparse rewards, holds an episodic memory to store the historical informati…

Cited by 1SourceScholar
2023

Task2Morph: Differentiable Task-Inspired Framework for Contact-Aware Robot Design

IROS 2023poster

Optimizing the morphologies and the controllers that adapt to various tasks is a critical issue in the field of robot design, aka. embodied intelligence. Previous works typically model it as a joint optimization problem and use search-based methods to find the optimal solution in the morphology spac…

Cited by 1SourceScholar
2022

PolarMesh: A Star-Convex 3D Shape Approximation for Object Pose Estimation

RA-L 2022

In this letter, we introduce PolarMesh as a star-convex approximation of a 3D object based on spherical projection and can be applied to monocular object pose and shape estimation. The proposed PolarMesh can be stored in a discrete 2D map that allows a trivial conversion between it and the object su

Cited by 11SourceScholar
2021

BT Expansion: a Sound and Complete Algorithm for Behavior Planning of Intelligent Robots with Behavior Trees

AAAI 2021technical

Behavior Trees (BTs) have attracted much attention in the robotics field in recent years, which generalize existing control architectures and bring unique advantages for building robot systems. Automated synthesis of BTs can reduce human workload and build behavior models for complex tasks beyond th…

2021

Dec-SGTS: Decentralized Sub-Goal Tree Search for Multi-Agent Coordination

AAAI 2021technical

Multi-agent coordination tends to benefit from efficient communication, where cooperation often happens based on exchanging information about what the agents intend to do, i.e. intention sharing. It becomes a key problem to model the intention by some proper abstraction. Currently, it is either too…