{"title":"TRON 2","description":null,"products":[{"product_id":"limx-dynamics-tron2-three-in-one","title":"LimX Dynamics TRON2 Three-in-one - modular robotic platform, 3-in-1","description":"\u003cdiv style=\"margin: 24px 0; padding: 22px; background: #f7f7f7; border: 1px solid #dddddd; border-radius: 10px; box-sizing: border-box; font-family: Arial, Helvetica, sans-serif; color: #333333; line-height: 1.6;\"\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch2 style=\"margin: 0 0 14px 0; font-size: 26px; line-height: 1.3; color: #333333;\"\u003eLimX Dynamics TRON2 Three-in-one - Modular 3-in-1 Platform for Robotics Research\u003c\/h2\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eThe \u003cstrong\u003eLimX Dynamics TRON2 Three-in-one\u003c\/strong\u003e is a modular robotics platform for research, embodied AI, and vision-language-action applications. The EDU Three-in-one package combines three interchangeable configurations in one system: \u003cstrong\u003eSole\u003c\/strong\u003e with classic feet, \u003cstrong\u003eWheeled Legs\u003c\/strong\u003e with wheel-driven legs, and \u003cstrong\u003eDual Arms\u003c\/strong\u003e for complex manipulation tasks.\u003c\/p\u003e \u003cp style=\"margin: 0;\"\u003eWith its open software architecture featuring ROS1, ROS2, Python, and high-level and low-level access, TRON2 is suitable for demanding research projects, Sim2Real workflows, and the development of custom locomotion, perception, and manipulation algorithms.\u003c\/p\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003e3-in-1 platform\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003e\n\u003cstrong\u003eSole:\u003c\/strong\u003e Classic feet for walking-based locomotion\u003c\/li\u003e \u003cli\u003e\n\u003cstrong\u003eWheeled Legs:\u003c\/strong\u003e Wheel-driven legs for fast mobile movement\u003c\/li\u003e \u003cli\u003e\n\u003cstrong\u003eDual Arms:\u003c\/strong\u003e Dual-arm system for manipulation and VLA applications\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eHighlights\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eThree modular, interchangeable configurations in one EDU package\u003c\/li\u003e \u003cli\u003e7 DoF per arm and 5 DoF per leg\u003c\/li\u003e \u003cli\u003eActive vision head with 2 DoF\u003c\/li\u003e \u003cli\u003eSpeeds of up to 5 m\/s in the Wheeled configuration\u003c\/li\u003e \u003cli\u003eClimbing capability of up to 30°\u003c\/li\u003e \u003cli\u003eDual Arms with a 70 cm span and a total payload of 10 kg\u003c\/li\u003e \u003cli\u003eRGBD cameras on the waist, head, and wrists in the Dual Arms configuration\u003c\/li\u003e \u003cli\u003eIntel Core i7-1165G7 computing unit\u003c\/li\u003e \u003cli\u003eOpen SDK with ROS1, ROS2, and Python\u003c\/li\u003e \u003cli\u003eURDF models for Sim2Real workflows\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eMobility and manipulation\u003c\/h3\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eThe modular design enables switching between different research tasks. According to the product specifications, TRON2 reaches speeds of up to 5 m\/s with Wheeled Legs and handles inclines of up to 30°. Two arm modules with 7 degrees of freedom each are available for manipulation tasks.\u003c\/p\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003e5 DoF per leg\u003c\/li\u003e \u003cli\u003e7 DoF per arm\u003c\/li\u003e \u003cli\u003e2 DoF in the active vision head\u003c\/li\u003e \u003cli\u003eDual-arm span: 70 cm\u003c\/li\u003e \u003cli\u003ePayload: 5 kg per arm, 10 kg total\u003c\/li\u003e \u003cli\u003eRepeatability: ±0.5 mm\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eSensing and computing power\u003c\/h3\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eFor perception and AI computations, TRON2 combines an Intel Core i7-1165G7 computing unit with multimodal sensors. Depending on the configuration, RGBD cameras are located at the waist, head, and wrists. An IMU complements motion tracking.\u003c\/p\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eIntel Core i7-1165G7, up to 2.80 GHz\u003c\/li\u003e \u003cli\u003eRGBD camera on the head\u003c\/li\u003e \u003cli\u003eRGBD camera at the waist\u003c\/li\u003e \u003cli\u003eRGBD cameras on the wrists with Dual Arms\u003c\/li\u003e \u003cli\u003eIMU for motion tracking\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eOpen software architecture\u003c\/h3\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eTRON2 is designed for research and development projects with direct system access. The open SDK enables both high-level and low-level control and supports the integration of existing robotics and AI workflows.\u003c\/p\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eROS1 support\u003c\/li\u003e \u003cli\u003eROS2 support\u003c\/li\u003e \u003cli\u003ePython support\u003c\/li\u003e \u003cli\u003eHigh-level control\u003c\/li\u003e \u003cli\u003eLow-level control\u003c\/li\u003e \u003cli\u003eOptimized URDF models for simulation and Sim2Real\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eTypical applications\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eEmbodied AI research\u003c\/li\u003e \u003cli\u003eVision-language-action research\u003c\/li\u003e \u003cli\u003eRobotic manipulation\u003c\/li\u003e \u003cli\u003eMobile robotics and all-terrain locomotion\u003c\/li\u003e \u003cli\u003eSim2Real research\u003c\/li\u003e \u003cli\u003eDevelopment of custom motion and control algorithms\u003c\/li\u003e \u003cli\u003eUniversity research and teaching\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 14px 0; font-size: 21px; color: #333333;\"\u003eTechnical specifications\u003c\/h3\u003e \u003cdiv style=\"overflow-x: auto;\"\u003e \u003ctable style=\"width: 100%; border-collapse: collapse; min-width: 680px;\"\u003e \u003cthead\u003e \u003ctr\u003e\n\u003cth style=\"padding: 11px 12px; background: #478a84; color: #ffffff; text-align: left; border: 1px solid #d5d5d5;\"\u003eCategory\u003c\/th\u003e\n\u003cth style=\"padding: 11px 12px; background: #478a84; color: #ffffff; text-align: left; border: 1px solid #d5d5d5;\"\u003eFeature\u003c\/th\u003e\n\u003cth style=\"padding: 11px 12px; background: #478a84; color: #ffffff; text-align: left; border: 1px solid #d5d5d5;\"\u003eSpecification\u003c\/th\u003e\n\u003c\/tr\u003e \u003c\/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSystem\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eProduct\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eLimX Dynamics TRON2 Three-in-one\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSystem\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eConfigurations\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSole, Wheeled Legs, Dual Arms\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eKinematics\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eDegrees of freedom per arm\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e7 DoF\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eKinematics\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eDegrees of freedom per leg\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e5 DoF\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eKinematics\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eVision head\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e2 DoF, active\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eMobility\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eMaximum speed\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eUp to 5 m\/s in Wheeled configuration\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eMobility\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eClimbing ability\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eUp to 30°\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eManipulation\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eDual-arm reach\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e70 cm\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eManipulation\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003ePayload per arm\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e5 kg\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eManipulation\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eTotal payload, Dual Arms\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e10 kg\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003ePrecision\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eRepeatability\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e±0.5 mm\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSensors\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eRGBD cameras\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eWaist, head, and wrists with Dual Arms\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSensors\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eIMU\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eIntegrated\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eComputing performance\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eProcessor\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eIntel Core i7-1165G7\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eComputing performance\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eClock speed\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eUp to 2.80 GHz\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003ePower\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eBattery\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e46.8 V lithium battery, 9 Ah\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003ePower\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eFast charging\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eFrom 20% to 80% in 30 minutes\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSDK\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eOpen SDK with high-level and low-level access\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eFrameworks\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eROS1, ROS2, Python\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSimulation\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eURDF models for Sim2Real workflows\u003c\/td\u003e \u003c\/tr\u003e \u003c\/tbody\u003e \u003c\/table\u003e \u003c\/div\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eScope of delivery\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003e1 x TRON2 Core system\u003c\/li\u003e \u003cli\u003e2 x arm modules (Dual Arms)\u003c\/li\u003e \u003cli\u003e1 x set of wheeled legs (Wheeled Legs)\u003c\/li\u003e \u003cli\u003e1 x set of standard feet (Sole)\u003c\/li\u003e \u003cli\u003eHigh-performance battery including fast charger\u003c\/li\u003e \u003cli\u003eComprehensive sensor kit with head, waist, and wrist cameras\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003c\/div\u003e","brand":"LimX Dynamics","offers":[{"title":"Default Title","offer_id":66042945798493,"sku":"F27211460","price":38999.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1074\/5649\/5965\/files\/limx-dynamics-tron2-three-in-one-funduino-3769715.png?v=1791482698"},{"product_id":"limx-dynamics-tron2-dual-arm","title":"LimX Dynamics TRON2 Dual Arm - research platform, 14 DoF","description":"\u003cdiv style=\"margin: 24px 0; padding: 22px; background: #f7f7f7; border: 1px solid #dddddd; border-radius: 10px; box-sizing: border-box; font-family: Arial, Helvetica, sans-serif; color: #333333; line-height: 1.6;\"\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px;\"\u003e \u003ch2 style=\"margin: 0 0 14px 0; font-size: 26px; color: #333333;\"\u003eLimX Dynamics TRON2 Dual Arm - Research platform for manipulation and teleoperation\u003c\/h2\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eThe \u003cstrong\u003eLimX Dynamics TRON2 Dual Arm\u003c\/strong\u003e is a specialized research platform for physical manipulation, teleoperation, and AI-assisted interaction. Two integrated robotic arms with a total of 14 degrees of freedom enable complex movements and are particularly suitable for research into vision-language-action, human demonstration, and robotic manipulation.\u003c\/p\u003e \u003cp style=\"margin: 0;\"\u003eRGBD cameras on the head, waist, and wrists support visual perception. The open SDK provides high-level and low-level access and supports Python, ROS2, and URDF-based Sim2Real workflows.\u003c\/p\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px;\"\u003eHighlights\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003e14 degrees of freedom in total, 7 DoF per arm\u003c\/li\u003e \u003cli\u003eSpherical wrist design for complex movements in confined spaces\u003c\/li\u003e \u003cli\u003eTeleoperation latency of approx. 100 ms\u003c\/li\u003e \u003cli\u003eEnd-effector speed of up to 5 m\/s\u003c\/li\u003e \u003cli\u003eEnd-effector acceleration of up to 36 m\/s²\u003c\/li\u003e \u003cli\u003eRGBD cameras on the head, waist, and wrists\u003c\/li\u003e \u003cli\u003e11th Gen Intel Core i7-1165G7\u003c\/li\u003e \u003cli\u003eOpen SDK with high-level and low-level access\u003c\/li\u003e \u003cli\u003ePython and ROS2 compatibility\u003c\/li\u003e \u003cli\u003eURDF models for Sim2Real workflows\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px;\"\u003eDual-arm manipulation and teleoperation\u003c\/h3\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eEach arm has 7 degrees of freedom. The spherical wrist design supports flexible movements and maneuvers in spatially constrained environments. A specified teleoperation latency of approx. 100 ms enables direct control for demonstration data and research tasks.\u003c\/p\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003e7 DoF per arm\u003c\/li\u003e \u003cli\u003e14 DoF in the dual-arm system\u003c\/li\u003e \u003cli\u003eTeleoperation latency: approx. 100 ms\u003c\/li\u003e \u003cli\u003eMaximum end-effector speed: 5 m\/s\u003c\/li\u003e \u003cli\u003eMaximum end-effector acceleration: 36 m\/s²\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px;\"\u003eOpen developer ecosystem\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eHigh-level control\u003c\/li\u003e \u003cli\u003eLow-level control\u003c\/li\u003e \u003cli\u003ePython support\u003c\/li\u003e \u003cli\u003eROS2 compatibility\u003c\/li\u003e \u003cli\u003eOptimized URDF models for Sim2Real workflows\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px;\"\u003eTypical applications\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eVision-language-action research\u003c\/li\u003e \u003cli\u003eRobotic manipulation\u003c\/li\u003e \u003cli\u003eTeleoperation and human demonstration data\u003c\/li\u003e \u003cli\u003eTraining AI models for physical interaction\u003c\/li\u003e \u003cli\u003eComputer vision and motion planning\u003c\/li\u003e \u003cli\u003eSim2Real research\u003c\/li\u003e \u003cli\u003eUniversity research and teaching\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px;\"\u003e \u003ch3 style=\"margin: 0 0 14px 0; font-size: 21px;\"\u003eTechnical specifications\u003c\/h3\u003e \u003cdiv style=\"overflow-x: auto;\"\u003e \u003ctable style=\"width: 100%; border-collapse: collapse; min-width: 680px;\"\u003e \u003cthead\u003e \u003ctr\u003e\n\u003cth style=\"padding: 11px 12px; background: #478a84; color: #ffffff; text-align: left; border: 1px solid #d5d5d5;\"\u003eCategory\u003c\/th\u003e\n\u003cth style=\"padding: 11px 12px; background: #478a84; color: #ffffff; text-align: left; border: 1px solid #d5d5d5;\"\u003eFeature\u003c\/th\u003e\n\u003cth style=\"padding: 11px 12px; background: #478a84; color: #ffffff; text-align: left; border: 1px solid #d5d5d5;\"\u003eSpecification\u003c\/th\u003e\n\u003c\/tr\u003e \u003c\/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eKinematics\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eTotal degrees of freedom\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e14 DoF\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eKinematics\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eDegrees of freedom per arm\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e7 DoF\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eKinematics\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eWrist\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSpherical design\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eManipulation\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eMax. end-effector speed\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e5 m\/s\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eManipulation\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eMax. end-effector acceleration\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e36 m\/s²\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eTeleoperation\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eLatency\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eapprox. 100 ms\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSensors\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eRGBD cameras\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eHead, waist, and wrists\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eComputing power\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eProcessor\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e11th Gen Intel Core i7-1165G7\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eEnergy\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eBattery\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e46.8 V lithium battery\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eEnergy\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eFast charging\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eFrom 20% to 80% in 30 minutes\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSDK\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eOpen SDK\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eControl\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eHigh-level and low-level access\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eCompatibility\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003ePython, ROS2\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSimulation\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eOptimized URDF models for Sim2Real workflows\u003c\/td\u003e \u003c\/tr\u003e \u003c\/tbody\u003e \u003c\/table\u003e \u003c\/div\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px;\"\u003eScope of delivery\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003e1 x TRON2 Core system\u003c\/li\u003e \u003cli\u003e2 x integrated arm modules with 7 DoF each\u003c\/li\u003e \u003cli\u003eComprehensive sensor kit including dedicated wrist-mounted RGBD cameras\u003c\/li\u003e \u003cli\u003eHigh-performance battery\u003c\/li\u003e \u003cli\u003eFast charger\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003c\/div\u003e","brand":"LimX Dynamics","offers":[{"title":"Default Title","offer_id":66042946781533,"sku":"F27211461","price":26999.01,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1074\/5649\/5965\/files\/limx-dynamics-tron2-dual-arm-funduino-6977588.png?v=1791482699"},{"product_id":"limx-dynamics-tron2-two-in-one","title":"LimX Dynamics TRON2 two-in-one - research robot, Sole and Wheeled Legs","description":"\u003cdiv style=\"margin: 24px 0; padding: 22px; background: #f7f7f7; border: 1px solid #dddddd; border-radius: 10px; box-sizing: border-box; font-family: Arial, Helvetica, sans-serif; color: #333333; line-height: 1.6;\"\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch2 style=\"margin: 0 0 14px 0; font-size: 26px; line-height: 1.3; color: #333333;\"\u003eLimX Dynamics TRON2 two-in-one - Modular platform for mobile robotics research\u003c\/h2\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eThe \u003cstrong\u003eLimX Dynamics TRON2 two-in-one\u003c\/strong\u003e is a modular research platform for developing advanced locomotion and navigation algorithms. The system combines two specialized movement modes in one platform: \u003cstrong\u003eSole\u003c\/strong\u003e for legged mobility and stair climbing, and \u003cstrong\u003eWheeled Legs\u003c\/strong\u003e for fast and efficient wheel-assisted mobility.\u003c\/p\u003e \u003cp style=\"margin: 0;\"\u003eWith speeds of up to 5 m\/s in the Wheeled configuration, a payload of up to 30 kg on level ground, a 30° climbing ability, and an open Sim2Real environment, TRON2 two-in-one is suitable for research into mobile robotics, perception, navigation, and embodied AI.\u003c\/p\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003e2-in-1 platform\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003e\n\u003cstrong\u003eSole:\u003c\/strong\u003e standard feet for precise walking and stair climbing\u003c\/li\u003e \u003cli\u003e\n\u003cstrong\u003eWheeled Legs:\u003c\/strong\u003e wheel-driven legs for fast mobile movement\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eHighlights\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eTwo modular, interchangeable mobility configurations\u003c\/li\u003e \u003cli\u003e5 degrees of freedom per leg\u003c\/li\u003e \u003cli\u003eActive head with 2 DoF\u003c\/li\u003e \u003cli\u003eUp to 5 m\/s in the Wheeled configuration\u003c\/li\u003e \u003cli\u003eUp to 30 kg payload on level ground\u003c\/li\u003e \u003cli\u003eClimbing ability up to 30°\u003c\/li\u003e \u003cli\u003eRGBD cameras on the head and waist\u003c\/li\u003e \u003cli\u003e11th-generation Intel Core i7-1165G7\u003c\/li\u003e \u003cli\u003e46.8 V battery with 9 Ah\u003c\/li\u003e \u003cli\u003eFast charging from 20% to 80% in 30 minutes\u003c\/li\u003e \u003cli\u003eOpen SDK for research and development projects\u003c\/li\u003e \u003cli\u003eSupport for Gazebo, MuJoCo, and NVIDIA Isaac Sim\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eMobility and all-terrain capability\u003c\/h3\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eBy switching between Sole and Wheeled Legs, TRON2 two-in-one can cover different research tasks. The Sole configuration is designed for legged mobility and stair climbing. The Wheeled configuration combines leg mechanics with wheel-assisted mobility for higher speeds.\u003c\/p\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eMaximum speed: up to 5 m\/s in the Wheeled configuration\u003c\/li\u003e \u003cli\u003ePayload: up to 30 kg on level ground\u003c\/li\u003e \u003cli\u003eClimbing ability: up to 30°\u003c\/li\u003e \u003cli\u003e5 DoF per leg\u003c\/li\u003e \u003cli\u003e2 DoF in the active head\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eSensors and computing performance\u003c\/h3\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eRGBD cameras on the head and waist support real-time perception and obstacle detection. An 11th Gen Intel Core i7-1165G7 processor is available for processing directly on the robot.\u003c\/p\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eRGBD camera on the head\u003c\/li\u003e \u003cli\u003eRGBD camera at the waist\u003c\/li\u003e \u003cli\u003eIntel Core i7-1165G7\u003c\/li\u003e \u003cli\u003eOnboard computing power for perception, navigation and inference\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eOpen software architecture and Sim2Real\u003c\/h3\u003e \u003cp style=\"margin: 0 0 12px 0;\"\u003eThe open SDK supports the workflow from data collection and simulation through transfer to real hardware. This makes TRON2 two-in-one suitable for developing and testing your own navigation, locomotion and AI algorithms.\u003c\/p\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eFully open SDK\u003c\/li\u003e \u003cli\u003eSupport for Gazebo\u003c\/li\u003e \u003cli\u003eSupport for MuJoCo\u003c\/li\u003e \u003cli\u003eSupport for NVIDIA Isaac Sim\u003c\/li\u003e \u003cli\u003eSim2Real workflows from training to hardware inference\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eTypical applications\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003eMobile robotics research\u003c\/li\u003e \u003cli\u003eLocomotion and navigation algorithms\u003c\/li\u003e \u003cli\u003eStair climbing and walking-based mobility\u003c\/li\u003e \u003cli\u003eHigh-speed wheeled mobility\u003c\/li\u003e \u003cli\u003eEmbodied AI\u003c\/li\u003e \u003cli\u003eSim2Real development\u003c\/li\u003e \u003cli\u003eUniversity research and teaching\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; margin-bottom: 18px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 14px 0; font-size: 21px; color: #333333;\"\u003eTechnical data\u003c\/h3\u003e \u003cdiv style=\"overflow-x: auto;\"\u003e \u003ctable style=\"width: 100%; border-collapse: collapse; min-width: 680px;\"\u003e \u003cthead\u003e \u003ctr\u003e\n\u003cth style=\"padding: 11px 12px; background: #478a84; color: #ffffff; text-align: left; border: 1px solid #d5d5d5;\"\u003eCategory\u003c\/th\u003e\n\u003cth style=\"padding: 11px 12px; background: #478a84; color: #ffffff; text-align: left; border: 1px solid #d5d5d5;\"\u003eFeature\u003c\/th\u003e\n\u003cth style=\"padding: 11px 12px; background: #478a84; color: #ffffff; text-align: left; border: 1px solid #d5d5d5;\"\u003eSpecification\u003c\/th\u003e\n\u003c\/tr\u003e \u003c\/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSystem\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eProduct\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eLimX Dynamics TRON2 two-in-one\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSystem\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eConfigurations\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSole, Wheeled Legs\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eKinematics\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eDegrees of freedom per leg\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e5 DoF\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eKinematics\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eActive head\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e2 DoF\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eMobility\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eMaximum speed\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eUp to 5 m\/s in the Wheeled configuration\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eMobility\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003ePayload\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eUp to 30 kg on level ground\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eMobility\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eClimbing ability\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eUp to 30°\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSensors\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eRGBD cameras\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eHead and waist\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eComputing performance\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eProcessor\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e11th Gen Intel Core i7-1165G7\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eEnergy\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eBattery\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003e46.8 V, 9 Ah\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eEnergy\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eFast charging\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eFrom 20% to 80% in 30 minutes\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSDK\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eFully open SDK\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSimulation\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eGazebo, MuJoCo, NVIDIA Isaac Sim\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eSoftware\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eWorkflow\u003c\/td\u003e \u003ctd style=\"padding: 10px 12px; border: 1px solid #dddddd;\"\u003eData collection, training, Sim2Real and inference\u003c\/td\u003e \u003c\/tr\u003e \u003c\/tbody\u003e \u003c\/table\u003e \u003c\/div\u003e \u003c\/div\u003e \u003cdiv style=\"background: #ffffff; padding: 22px; border-radius: 10px; box-sizing: border-box;\"\u003e \u003ch3 style=\"margin: 0 0 12px 0; font-size: 21px; color: #333333;\"\u003eScope of delivery\u003c\/h3\u003e \u003cul style=\"margin: 0; padding-left: 22px;\"\u003e \u003cli\u003e1 x TRON2 Core system\u003c\/li\u003e \u003cli\u003e1 x set of wheeled legs (Wheeled Legs)\u003c\/li\u003e \u003cli\u003e1 x set of standard feet (Sole)\u003c\/li\u003e \u003cli\u003eIntegrated sensors with head and waist cameras\u003c\/li\u003e \u003cli\u003eHigh-performance battery including fast charger\u003c\/li\u003e \u003cli\u003eAccess to SDK and technical documentation\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003c\/div\u003e","brand":"LimX Dynamics","offers":[{"title":"Default Title","offer_id":66042947535197,"sku":"F27211462","price":24999.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1074\/5649\/5965\/files\/limx-dynamics-tron2-two-in-one-funduino-3766501.png?v=1791482717"}],"url":"https:\/\/funduino.com\/en\/collections\/tron-2.oembed","provider":"Funduino","version":"1.0","type":"link"}