Robo-Insight #4

Robo-Insight #4

Source: OpenAI’s DALL·E 2 with prompt “a hyperrealistic picture of a robot reading the news on a laptop at a coffee shop”

Welcome to the 4th edition of Robo-Insight, a biweekly robotics news update! In this post, we are excited to share a range of new advancements in the field and highlight robots’ progress in areas like mobile applications, cleaning, underwater mining, flexibility, human well-being, depression treatments, and human interactions.

Simplified mobile robot behavior adaptations

In the world of system adaptions, researchers from Eindhoven University of Technology have introduced a methodology that bridges the gap between application developers and control engineers in the context of mobile robots’ behavior adaptation. This approach leverages symbolic descriptions of robots’ behavior, known as “behavior semantics,” and translates them into control actions through a “semantic map.” This innovation aims to simplify motion control programming for autonomous mobile robot applications and facilitate integration across various vendors’ control software. By establishing a structured interaction layer between application, interaction, and control layers, this methodology could streamline the complexity of mobile robot applications, potentially leading to more efficient underground exploration and navigation systems.

The frontal perspective of the mobile platform (showcases hardware components with blue arrows). Source.

New robot for household clean-ups

Speaking of helpful robots, Princeton University has created a robot named TidyBot to address the challenge of household tidying. Unlike simple tasks such as moving objects, real-world cleanup requires a robot to differentiate between objects, place them correctly, and avoid damaging them. TidyBot accomplishes this through a combination of physical dexterity, visual recognition, and language understanding. Equipped with a mobile robotic arm, a vision model, and a language model, TidyBot can identify objects, place them in designated locations, and even infer proper actions with an 85% accuracy rate. The success of TidyBot demonstrates its potential to handle complex household tasks.

TidyBot in work. Source.

Deep sea mining robots

Shifting our focus to underwater environments, researchers are addressing the efficiency hurdles faced in deep-sea mining through innovative path planning for autonomous robotic mining vehicles. With deep-sea manganese nodules holding significant potential, these robotic vehicles are essential for their collection. By refining path planning methods, the researchers aim to improve the efficiency of these vehicles in traversing challenging underwater terrains while avoiding obstacles. This development could lead to more effective and responsible resource extraction from the ocean floor, contributing to the sustainable utilization of valuable mineral resources.

Diagram depicting the operational framework of the deep-sea mining system. Source.

Advanced soft robots with dexterity and flexibility

In regards to the field of robotic motion, recently researchers from Shanghai Jiao Tong University have developed small-scale soft robots with remarkable dexterity, enabling immediate and reversible changes in motion direction and shape reconfiguration. These robots, powered by an active dielectric elastomer artificial muscle and a unique chiral-lattice foot design, can change direction during fast movement with a single voltage input. The chiral-lattice foot generates various locomotion behaviors, including forward, backward, and circular motion, by adjusting voltage frequencies. Additionally, combining this structural design with shape memory materials allows the robots to perform complex tasks like navigating narrow tunnels or forming specific trajectories. This innovation opens the door to next-generation autonomous soft robots capable of versatile locomotion.

The soft robot achieves circular motion in either right or left directions by positioning the lattice foot towards the respective sides. Source.

Robotic dogs utilized to comfort patients

Turning our focus to robot use in the healthcare field, Stanford students, along with researchers and doctors, have partnered with AI and robotics industry leaders to showcase new robotic dogs designed to interact with pediatric patients at Lucile Packard Children’s Hospital. Patients at the hospital had the opportunity to engage with the playful robots, demonstrating the potential benefits of these mechanical pets for children’s well-being during their hospital stays. The robots, called Pupper, were developed by undergraduate engineering students and operated using handheld controllers. The goal of the demonstration was to study the interaction between the robots and pediatric patients, exploring ways to enhance the clinical experience and reduce anxiety.

A patient playing with the robotic dog. Source.

Robotic innovations could help with depression

Along the same lines as improving well-being, a recent pilot study has explored the potential benefits of using robotics in transcranial magnetic stimulation (TMS) for treating depression. Researchers led by Hyunsoo Shin developed a custom TMS robot designed to improve the accuracy of TMS coil placement on the brain, a critical aspect of effective treatment. By employing the robotic system, they reduced preparation time by 53% and significantly minimized errors in coil positioning. The study found comparable therapeutic effects on depression severity and regional cerebral blood flow (rCBF) between the robotic and manual TMS methods, shedding light on the potential of robotic assistance in enhancing the precision and efficiency of TMS treatments.

Configuration of the robotic repetitive transcranial magnetic stimulation (rTMS) within the treatment facility, and robotic positioning device for automated coil placement. Source.

Advanced robotic eye research

Finally, in the world of human-robot enhancement, a study conducted by researchers from various institutions has explored the potential of using robot eyes as predictive cues in human-robot interaction (HRI). The study aimed to understand whether and how the design of predictive robot eyes could enhance interactions between humans and robots. Four different types of eye designs were tested, including arrows, human eyes, and two anthropomorphic robot eye designs. The results indicated that abstract anthropomorphic robot eyes, which mimic certain aspects of human-like attention, were most effective at directing participants’ attention and triggering reflexive shifts. These findings suggest that incorporating abstract anthropomorphic eyes into robot design could improve the predictability of robot movements and enhance HRI.

The four types of stimuli. The first row showcases the human (left) and arrow (right) stimuli. The second row displays the abstract anthropomorphic robot eyes. Photograph of the questionnaire’s subject, the cooperative robot Sawyer. Source.

The continuous stream of progress seen across diverse domains underscores the adaptable and constantly progressing nature of robotics technology, revealing novel pathways for its incorporation across a spectrum of industries. The gradual advancement in the realm of robotics reflects persistent efforts and hints at the potential implications these strides might hold for the future.


  1. Chen, H. L., Hendrikx, B., Torta, E., Bruyninckx, H., & van de Molengraft, R. (2023, July 10). Behavior adaptation for mobile robots via semantic map compositions of constraint-based controllers. Frontiers.
  2. Princeton Engineering – Engineers clean up with TidyBot. (n.d.). Princeton Engineering. Retrieved August 30, 2023,
  3. Xie, Y., Liu, C., Chen, X., Liu, G., Leng, D., Pan, W., & Shao, S. (2023, July 12). Research on path planning of autonomous manganese nodule mining vehicle based on lifting mining system. Frontiers.
  4. Wang, D., Zhao, B., Li, X., Dong, L., Zhang, M., Zou, J., & Gu, G. (2023). Dexterous electrical-driven soft robots with reconfigurable chiral-lattice foot design. Nature Communications14(1), 5067.
  5. University, S. (2023, August 1). Robo-dogs unleash joy at Stanford hospital. Stanford Report.
  6. Shin, H., Jeong, H., Ryu, W., Lee, G., Lee, J., Kim, D., Song, I.-U., Chung, Y.-A., & Lee, S. (2023). Robotic transcranial magnetic stimulation in the treatment of depression: a pilot study. Scientific Reports13(1), 14074.
  7. Onnasch, L., Schweidler, P., & Schmidt, H. (2023, July 3). The potential of robot eyes as predictive cues in HRI-an eye-tracking study. Frontiers.
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