| 1 |
GG-LLM: Geometrically Grounding Large Language Models for Zero-shot Human Activity Forecasting in Human-Aware Task Planning |
提出GG-LLM以解决人类活动预测中的数据依赖问题 |
motion planning semantic map human motion |
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| 2 |
Large Trajectory Models are Scalable Motion Predictors and Planners |
提出State Transformer以解决自主驾驶中的运动预测与规划问题 |
motion planning motion prediction large language model |
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| 3 |
Rule-Based Lloyd Algorithm for Multi-Robot Motion Planning and Control with Safety and Convergence Guarantees |
提出基于规则的Lloyd算法以解决多机器人运动规划问题 |
motion planning |
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| 4 |
Explaining the Decisions of Deep Policy Networks for Robotic Manipulations |
提出输入归因方法以提升机器人策略网络的透明性 |
manipulation |
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| 5 |
DEFT: Dexterous Fine-Tuning for Real-World Hand Policies |
提出DEFT以解决复杂物体操控中的数据效率问题 |
manipulation dexterous manipulation |
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