Abstract
My capstone team spent the Fall 2025 semester constructing a robot capable of playing Jenga autonomously. Our team received the Dobot Magician robotic arm, which was named TALOS, from our academic advisor. TALOS’ goal was to be able to remove a block from a Jenga tower and subsequently place it at the top. According to Dobot’s marketing materials, this robotic arm was easy to use and hardly required any programming. Furthermore, they claimed that their robotic arms were ready to use right out of the box, leading my team to believe that we would have plenty of time during our fifteen-week semester to develop the fun aspect of playing Jenga via computer vision and other robotic-related topics. However, rather than spending the majority of our attention on these aspects, we concentrated on them for around half the time available. This was due to unexpected complications, such as being unable to install Dobot’s official SDKs on our Linux OS, which forced us to reverse-engineer the proprietary SDKs. Then we had to create custom software from scratch only to get the arm to respond to a command. Finally, we had to buy a motorized turntable to have extra access angles to the blocks on the tower’s side since, while TALOS has four degrees of freedom, the arm’s positioning capability was limited, preventing us from reaching any of them. After completing the construction of TALOS’ software and hardware capabilities, it successfully put a first block approximately 73% of the time; however, this declined when placing a second block, resulting in a 16.7% success rate. The reasons for this substantial drop in performance were mostly due to calibration issues with the robot’s y-axis positioning capability as well as a gripper lacking sufficient lateral force to grasp and move the blocks. These limitations were absent in the Dobot’s marketing materials.
The primary objective of my STS Research paper is to identify and investigate how the marketing language surrounding desktop collaborative robots (cobots), specifically the Dobot Magician, produces a perceived sense of accessibility by neglecting or failing to provide the tools to complete practical application. To investigate this, I applied Hart and Cap’s Critical Discourse Analysis framework to four different types of data: promotional/technical documentation provided by Dobot, comments and posts from online discussion forums commenting on their experiences with cobots, semi-structured interviews with members of UVA’s MARS robotics team, and the TALOS technical report. A general trend emerged in three areas: democratization, safety, and ease of use. Under “HIGH QUALIFICATION STANDARDS,” Dobot claims to have certification for CE, RoHS, and FCC. These certifications confirm that the equipment meets electromagnetic compatibility requirements and environmental compliances, but they do not address whether the device can be operated safely near an individual. Furthermore, the Dobot’s user manual explicitly warns that children should not use the device independently and that adult supervision is required at all times, yet this disclaimer does not appear in any marketing material. Dobot also refers to the Magician as a “cobot” despite the fact that it does not list the ISO/TS 15066, a standard that defines collaborative robots classification. The abundance of forum postings, workaround solutions provided by teams at both the University of Arts London and Carnegie Mellon University, and comments from interview participants from the MARS team all demonstrate that the amount of unspoken labor created here is not an anomaly. When users meet these issues, marketing has already developed a framework in which failure is blamed on the user rather than the difference between what the product claims to deliver and what it actually demands.
The relationship between these two projects turned out to be larger than I had anticipated. Making the transition into STS research after personally experiencing the consequences of misleading marketing claims proved to be crucial context for the forum discussions and interviews examined in this paper, since my capstone team faced remarkably similar circumstances. The research conducted provided a vital foundation for understanding the nature of our semester-long experience, which demonstrated that the challenges we faced were not uncommon occurrences of unfortunate events. On the contrary, they draw attention to a more general problem in which students and professors from all over the country continue to face difficulties when dealing with similar robotic products due to a lack of documentation. Ultimately, the STS research served as the framework for explaining the reason why these systemic patterns emerge, while the capstone project laid out concrete evidence to support their existence.
