Lifelong Path Planning with Kinematic Constraints for Multi-Agent Pickup and Delivery
Authors: Hang Ma, Wolfgang Hönig, T. K. Satish Kumar, Nora Ayanian, Sven Koenig7651-7658
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate its benefits for automated warehouses using both an agent simulator and a standard robot simulator. |
| Researcher Affiliation | Academia | Department of Computer Science University of Southern California |
| Pseudocode | Yes | Algorithm 1: SIPPw RT. |
| Open Source Code | No | The paper mentions 'Videos of sample experiments can be found at http://idm-lab.org/project-p.html' which is a project page, but it does not provide an explicit statement of code release or a direct link to the source code for the described methodology. |
| Open Datasets | No | The paper describes experiments conducted in a 'simulated warehouse environment' and does not provide concrete access information or citations for a publicly available or open dataset. |
| Dataset Splits | No | The paper describes simulation experiments with task frequencies and varying numbers of agents but does not specify training, validation, or test dataset splits, as it does not involve machine learning model training on a dataset in the typical sense. |
| Hardware Specification | Yes | We now report our experimental results on a 2.50 GHz Intel Core i5-2450M laptop with 6 GB RAM. |
| Software Dependencies | No | The paper mentions using the 'robot simulator V-REP (Rohmer, Singh, and Freese 2013)' but does not specify its version number or any other software dependencies with version information. |
| Experiment Setup | Yes | We use 30 agents (agts)... We use vfree = 1.00 m/s and vrot = π/2 = 1.57 rad/s. We generate one sequence of 1,000 tasks and insert them in the generated order into the system with a task frequency (task freq) of 2 tasks in the beginning of every second. (from Experiment 1) and Create2 robots have a cylindrical shape with radius 0.175 m and can reach a translational speed of 0.5 m/s and a rotational speed of 4.2 rad/s. We use vfree = 0.40 m/s, vtask = 0.20 m/s, vrot = π = 3.14 rad/s, and R = 0.40 m as conservative values... (from Experiment 4). |