小米、百度先后领投，这家开源人形机器人创企引爆资本圈

Core Viewpoint - RoboParty, a startup focused on open-source bipedal humanoid robots, has successfully completed two rounds of financing within a month, indicating strong investor interest and confidence in its business model and technology [2][3]. Group 1: Company Overview - RoboParty was founded in February 2025 in Shanghai, emphasizing a "open-source + platform" development approach, aiming to create low-cost, standardized, and reusable humanoid robot platforms [6]. - The company is the only one in China that has achieved full-stack open-source capabilities from algorithms and control to hardware integration in the bipedal humanoid robot sector [6]. - The founder, Huang Yi, is noted as the youngest CEO of a humanoid robot startup, having developed a walking robot, AlexBot, during his university years and later establishing RoboParty with a team of older students [6]. Group 2: Financing and Investment - RoboParty completed a seed + round of financing on December 16, 2023, with investments from prominent venture capital firms including SenseTime, Baidu Ventures, and Huaying Capital, alongside continued support from previous investors [2]. - The company had previously announced a multi-million dollar seed round on November 12, 2023, which was the largest seed round financing in the domestic bipedal humanoid robot sector to date [3]. Group 3: Product and Commercialization Progress - The company has already received orders for hundreds of units from listed companies, which it declined to ensure higher quality development in the future [7]. - RoboParty is currently developing its second-generation robot, exploring new materials and processes [8]. - The company aims to lower the barriers to developing embodied intelligence by providing open access to design documents, code, and deployment instructions [6]. Group 4: Industry Context - The embodied intelligence sector remains vibrant, with ongoing capital enthusiasm and a continuous influx of new startups, despite existing technical bottlenecks [12]. - There is a divide in the industry between hardware-focused companies and those emphasizing AI capabilities, leading to different commercialization strategies [13]. - Both camps face challenges, but there is no clear right or wrong approach, indicating a lack of consensus in the industry [14].