Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints
Authors: Masoumeh Mansouri, Bruno Lacerda, Nick Hawes, Federico Pecora
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate our approach on an industrial scenario, showing that it outperforms hand-crafted policies used in current practice. |
| Researcher Affiliation | Academia | 1 Orebro University, Sweden 2Oxford Robotics Institute, University of Oxford, UK |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any explicit statements about releasing source code for the described methodology or links to code repositories. |
| Open Datasets | No | The paper describes using a simulation environment to generate data for learning transition models, but does not provide concrete access information (link, DOI, specific citation with author/year for a public dataset) for this data or the simulation itself. |
| Dataset Splits | No | The paper describes generating data from simulations for fitting distributions, but does not provide specific dataset split information (e.g., percentages, sample counts, or references to predefined splits) needed to reproduce data partitioning. |
| Hardware Specification | No | The paper states 'our approach was run on a standard desktop pc', which lacks specific hardware details such as CPU/GPU models, memory, or other detailed computer specifications. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers (e.g., library names with versions or specific solver versions). |
| Experiment Setup | Yes | We use the simulation depicted in Fig. 2. 32 problems of the form n, PC, D are generated, where n is the number of robots, D is the disturbance profile, and PC is the number of seconds it takes the PC to fill a robot. The disturbance profile is a delay in seconds, applied to a robot as it navigates between any two locations, with a fixed probability of 0.5. Each policy is run for 15 times on each problem for 10 minutes each time. We halt the simulation before 10 minutes if there is no robot under the PC. |