5 papers · 1 filter
HELP: Hierarchical Embodied Language Planner for Household Tasks
Alexandr V. Korchemnyi, Anatoly O. Onishchenko, Eva A. Bakaeva +2
Embodied agents tasked with complex scenarios, whether in real or simulated environments, rely heavily on robust planning capabilities. When instructions are formulated in natural…
LookPlanGraph: Embodied Instruction Following Method with VLM Graph Augmentation
Anatoly O. Onishchenko, Alexey K. Kovalev, Aleksandr I. Panov
Methods that use Large Language Models (LLM) as planners for embodied instruction following tasks have become widespread. To successfully complete tasks, the LLM must be grounded i…
LERa: Replanning with Visual Feedback in Instruction Following
Svyatoslav Pchelintsev, Maxim Patratskiy, Anatoly Onishchenko +7
Large Language Models are increasingly used in robotics for task planning, but their reliance on textual inputs limits their adaptability to real-world changes and failures. To add…
Mind and Motion Aligned: A Joint Evaluation IsaacSim Benchmark for Task Planning and Low-Level Policies in Mobile Manipulation
Nikita Kachaev, Andrei Spiridonov, Andrey Gorodetsky +8
Benchmarks are crucial for evaluating progress in robotics and embodied AI. However, a significant gap exists between benchmarks designed for high-level language instruction follow…
VerifyLLM: LLM-Based Pre-Execution Task Plan Verification for Robots
Danil S. Grigorev, Alexey K. Kovalev, Aleksandr I. Panov
In the field of robotics, researchers face a critical challenge in ensuring reliable and efficient task planning. Verifying high-level task plans before execution significantly red…