{"id":"07f3f88b-7741-4a8b-ae47-3be722e0be0b","task_name":"task-franka-pickplace-multibase","task_version":1,"tournament_version":2,"task_gh":"https://github.com/nepher-ai/task-franka-pickplace-multibase","eval_gh":"https://github.com/nepher-ai/eval-nav","status":"active","stage":"contest","contest_start_time":1783068173,"contest_end_time":1783848173,"evaluation_start_time":1783848185,"evaluation_end_time":1783934585,"submit_window_start_time":1783761773,"reward_start_time":1784020985,"reward_end_time":1784064185,"has_public_eval":true,"current_eval_phase":"public","public_eval_end_time":1783844585,"public_eval_buffer_hours":1,"contest_start_block":8539388,"contest_end_block":8604388,"submit_window_start_block":8597188,"evaluation_start_block":8604389,"evaluation_end_block":8611589,"reward_start_block":8618789,"reward_end_block":8622389,"reward_block":8618789,"winner_agent_id":null,"winner_hotkey":null,"winner_score":null,"winner_approved":false,"winner_is_public":false,"winner_approved_at":null,"winner_approved_by":null,"is_test":false,"test_whitelist":null,"auto_start_next_id":null,"auto_start_next_task_name":null,"auto_start_next_task_version":null,"auto_start_next_tournament_version":null,"gallery_thumbnails":null,"gallery_videos":["https://6ae7e8c4cd5d23f4d4c33792e9fac740.r2.cloudflarestorage.com/tournament-gallery/gallery/f0d9a7fb-d33b-4070-a17d-902488b8d780.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=83a1ef9f9112dda54a8b68dd97b02299%2F20260706%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20260706T185657Z&X-Amz-Expires=86400&X-Amz-SignedHeaders=host&X-Amz-Signature=d79be1308e2c8ebd669ae94ae589243e02c7249bbefcb022b61b66c46b257abe"],"gallery":[{"id":"f0d9a7fb-d33b-4070-a17d-902488b8d780","title":"Franka Pick Place Multi Base","alt_text":null,"media_type":"video","content_type":"video/mp4","url":"https://6ae7e8c4cd5d23f4d4c33792e9fac740.r2.cloudflarestorage.com/tournament-gallery/gallery/f0d9a7fb-d33b-4070-a17d-902488b8d780.mp4?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=83a1ef9f9112dda54a8b68dd97b02299%2F20260706%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20260706T185657Z&X-Amz-Expires=86400&X-Amz-SignedHeaders=host&X-Amz-Signature=d79be1308e2c8ebd669ae94ae589243e02c7249bbefcb022b61b66c46b257abe","file_size":19953880,"width":null,"height":null,"display_order":0}],"created_at":"2026-07-03T08:42:56.769537","updated_at":"2026-07-03T14:56:53.065840","title":"Franka - Pick and Place - Multi Base - Phase 2","subtitle":"Train a Franka robot to pick and place objects from multiple randomized bases with robust manipulation policies.","overview":"Develop a robotic manipulation policy that enables a Franka Panda arm to reliably pick and place objects across multiple base configurations and randomized environments. The challenge focuses on generalization, precision, and success rate under varying object and container positions. The task is designed for Isaac Lab and EnvHub-based evaluation.","tags":["robotics","manipulation","franka","pick place","arm"],"difficulty":"beginner","is_featured":true,"cover_image_url":null,"browse_thumbnail_media_id":"432e3b41-87b1-407c-951a-ba0e645a957b","browse_thumbnail_url":"https://6ae7e8c4cd5d23f4d4c33792e9fac740.r2.cloudflarestorage.com/tournament-gallery/gallery/432e3b41-87b1-407c-951a-ba0e645a957b.png?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=83a1ef9f9112dda54a8b68dd97b02299%2F20260706%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20260706T185657Z&X-Amz-Expires=86400&X-Amz-SignedHeaders=host&X-Amz-Signature=cf5beb8fc4bc60b1d7fc1719fd269cfaa5a472f0ef324c568d1e4025aa2f64e0","subnet_config":{"network":"finney","subnet_uid":49,"contest_start_block":8539388,"contest_duration_blocks":65000,"evaluation_duration_blocks":7200,"submit_window_blocks":7200,"reward_start_blocks":7200,"reward_duration_blocks":3600,"max_submission_size":100},"statistics":{"agents_count":16,"participants_count":11,"eligible_count":0,"validator_count":4,"average_score":0.2105646913580247,"top_score":0.2964555555555555,"score_phase":"public"},"subnet_config_yaml":"subnet:\n  network: \"finney\"\n  subnet_uid: 49\n  contest_start_block: 8539388\n  contest_duration_blocks: 65000\n  evaluation_duration_blocks: 7200\n  submit_window_blocks: 7200\n  reward_start_blocks: 7200\n  reward_duration_blocks: 3600\n  max_submission_size: 100","eval_config_yaml":"# Evaluation configuration for task-franka-pickplace-multibase\n\ntask_name: \"Nepher-Franka-PickPlace-HL-Multibase-EnvhubPlay-v0\"\ntask_module: \"franka_pickplace_multibase\"\ncategory: \"manipulation\"\n\nenv_scenes:\n  - env_id: \"franka-pickplace-multibase-v1\"\n    scene: 0\n\nseeds:\n  - 42\n\nnum_episodes: 3\nmax_episode_steps: 1500\n\n\nmax_episode_time_s: 30.0\n\nnum_envs: 30\n\ntask_type: \"manipulation.pick_place\"\nscoring_version: \"v2\"\n\nlog_dir: \"logs/franka-pickplace-multibase-hl\"\nenable_logging: true\nenable_cameras: false\ntimeout_seconds: null\npolicy_path: \"default\"\n","public_eval_config_yaml":"# Evaluation configuration for task-franka-pickplace-multibase\n\ntask_name: \"Nepher-Franka-PickPlace-HL-Multibase-EnvhubPlay-v0\"\ntask_module: \"franka_pickplace_multibase\"\ncategory: \"manipulation\"\n\nenv_scenes:\n  - env_id: \"franka-pickplace-multibase-sample\"\n    scene: 0\n\nseeds:\n  - 42\n\nnum_episodes: 3\nmax_episode_steps: 1500\n\n\nmax_episode_time_s: 30.0\n\nnum_envs: 30\n\ntask_type: \"manipulation.pick_place\"\nscoring_version: \"v2\"\n\nlog_dir: \"logs/franka-pickplace-multibase-hl\"\nenable_logging: true\nenable_cameras: false\ntimeout_seconds: null\npolicy_path: \"default\"\n","is_active":true,"task_config":{"task_name":"task-franka-pickplace-multibase","task_version":1,"tournament_version":2,"active_task":true},"eval_config":{"task_name":"Nepher-Franka-PickPlace-HL-Multibase-EnvhubPlay-v0","task_module":"franka_pickplace_multibase","category":"manipulation","env_scenes":[{"env_id":"franka-pickplace-multibase-v1","scene":0}],"seeds":[42],"num_episodes":3,"max_episode_steps":1500,"max_episode_time_s":30.0,"num_envs":30,"task_type":"manipulation.pick_place","scoring_version":"v2","log_dir":"logs/franka-pickplace-multibase-hl","enable_logging":true,"enable_cameras":false,"timeout_seconds":null,"policy_path":"default"},"description":"# Franka Pick and Place – Multi Base\n\nWelcome to the **Franka Pick and Place – Multi Base** tournament challenge.\n\nIn this competition, participants must develop a robotic control policy capable of performing robust pick-and-place operations using a **Franka Panda manipulator** across multiple randomized base environments. The robot must detect, grasp, transport, and place target objects into a designated container while maintaining high success rates under varying scene configurations. \n\n## Challenge Objectives\n\nParticipants are expected to train a policy that can:\n\n* Reach target objects from diverse robot base positions.\n* Execute stable grasping motions.\n* Transport objects without dropping them.\n* Place objects accurately into the target container.\n* Generalize across unseen environment variations.\n\n## Environment Characteristics\n\nThe benchmark includes:\n\n* Multiple robot base configurations.\n* Randomized object placements.\n* Randomized container positions.\n* Physics-based simulation using NVIDIA Isaac Lab.\n* Evaluation through standardized EnvHub environments.\n\n## What Makes This Challenging?\n\nUnlike fixed pick-and-place benchmarks, the robot must learn policies that generalize across different spatial layouts. Success requires both robust manipulation and effective adaptation to environment variations.\n\nParticipants may utilize:\n\n* Reinforcement Learning\n* Imitation Learning\n* Hybrid approaches\n* Classical motion-planning-assisted learning\n\n## Goal\n\nAchieve the highest overall evaluation score by maximizing successful pick-and-place completion while minimizing failures and inefficient motions.","evaluation_description":"Submissions are evaluated using automated benchmark scenarios executed in hidden validation environments.\nFinal rankings are determined by the aggregate score across all evaluation scenarios. Hidden validation environments are used to prevent overfitting and encourage generalizable solutions.","rules":"The objective is to produce policies that generalize to unseen scenarios rather than memorizing fixed layouts.\n\nEvaluation Policy\n- Multiple submissions are allowed during the competition period.\n- Only the latest valid submission will be evaluated.\n- Final rankings are determined by official tournament evaluation results.","dataset_description":"The benchmark contains:\n\n- Franka Panda manipulator setup.\n- Pick-and-place environments.\n- Multiple base configurations.\n- Object and container randomization logic.\n\nParticipants are responsible for generating their own training data, demonstrations, or policies using the provided simulation environments.","faqs":[],"platform_faqs":[]}