{"url":"/dataset/telesim","name":"TeleSim","full_name":"TeleSim: A Network-Aware Testbed and Benchmark Dataset for Telerobotic Applications","description_markdown":"TeleSim is a network-aware hardware-in-the-loop dataset designed to evaluate the performance of telerobotic systems under varying network conditions. It includes 300 fine-manipulation trials using a 6-DoF robotic arm and simulated networks in OMNeT++. Each trial captures:\r\n\r\n- Network configuration (bandwidth, latency, jitter, packet loss)\r\n- Measured network metrics (throughput, delay, jitter, real packet loss)\r\n- Video quality (PSNR, SSIM)\r\n- Task performance (completion time, success rate)\r\n\r\nMotivation: Existing teleoperation datasets often ignore the impact of real-world network degradation. TeleSim fills this gap by systematically evaluating how adverse conditions affect visual perception and task execution.\r\n\r\nUse cases:\r\n- Benchmarking teleoperation performance\r\n- Designing adaptive control algorithms\r\n- Evaluating network resilience of robotic systems","description_withheld":null,"homepage":"https://github.com/ConnectedRoboticsLab/TeleSim","introduced_date":"2025-07-06","introduced_date_note":null,"introduced_by":{"paper":"/paper/telesim-a-network-aware-testbed-and-benchmark","title":"TeleSim: A Network-Aware Testbed and Benchmark Dataset for Telerobotic Applications","first_author":null,"url":null},"license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"modalities":[{"name":"Tabular","url":"/datasets/modality/tabular"}],"tasks":[{"name":"2-task Classification","url":"/task/2-task-classification","datasets_with_task":"/datasets/task/2-task-classification"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["TeleSim"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}