Here is the key idea of the video in a single sentence: Humanoid robots are rapidly advancing in design, capabilities, and functionality, but despite their impressive developments, they still face significant challenges and limitations that hinder their practical application and widespread adoption.
## Questions to inspire discussion.
Manis Glove Technology.
🖐️ Q: How does the Manis glove achieve accurate hand tracking? A: The glove tracks 25 degrees of freedom using inverse kinematics based on 6DOF per fingertip (position and orientation), enabling accurate motion capture even when fingertips are obscured.
🔌 Q: What hardware enables the Manis glove’s position tracking? A: The system uses transmitters at the base and receivers in fingertips to determine precise fingertip position relative to the transmitter, with simple calibration allowing different hand sizes as long as sensors stay in place.
📳 Q: How does the Manis glove provide haptic feedback? A: Haptic feedback at the PIP joints vibrates upon contact, enabling virtual world interaction and realistic surface contact simulation for teleoperation and clinical evaluations.
🎬 Q: What are the primary applications for the Manis glove? A: After 10 years of development with Hollywood motion capture origins, the glove shows potential for high-quality clinical evaluation data, robotics, and medical fields.
Boston Dynamics Atlas Design.
⚙️ Q: What actuator strategy does the new Atlas robot use? A: Atlas features 100-degree rotary actuators for elbow and knee, using only two unique actuators to enable part reuse for left and right limbs, prioritizing cost, complexity, and reliability for factory use.
🔧 Q: How quickly can Atlas limbs be serviced? A: Customers can swap limbs in under 5 minutes, with dramatically more reliable rotary actuators compared to linear ones, designed specifically for factory floors.
📦 Q: What are the trade-offs of reducing actuator SKU count? A: Reducing SKU count lowers costs at large volumes but may lead to over or under-actuation in certain joints, impacting performance and load-bearing capacity.
🏭 Q: Why might Hyundai succeed at varied actuator production? A: Hyundai’s expertise in building lines and working with suppliers could enable production of varied actuator types at scale, balancing manufacturing trade-offs with performance needs.
Mechanical Design Considerations.
🔄 Q: What are the issues with parallel mechanisms in humanoid waists? A: Parallel mechanisms in humanoid waist joints are prone to failure and torque transparency issues, making direct drive systems preferable for better control and reliability.
💪 Q: How does the Cyber Robo humanoid’s hip joint work? A: The SPU drive in hip area uses parallel actuation mechanism for rotary abduction, flexion, and waist rotation, with two rotary actuators at top of hip joint visible in X-ray view.
🦵 Q: What mechanism does Cyber Robo use for knee actuation? A: The knee actuator employs modified inverted Herkin’s mechanism to linearize torque curve, with abductor actuator on inner thigh above knee and flexor actuator on back of thigh.
🤚 Q: How is the Cyber Robo hand actuated? A: Forearm actuation utilizes 25 tendons actuated by single cylindrical unit, with five tendons per digit (two for abduction, three for flexion-extension in four fingers).
✋ Q: Why is wrist movement critical for humanoid dexterity? A: Wrist movement is essential for dexterity in tendon-driven hands, requiring actuators in wrist and forearm for proper function, with wrist acting as central link in kinematic chain, combining flexion-extension and radial-ulnar deviation.
Robot Training and AI
🤖 Q: When is reinforcement learning necessary for humanoid training? A: Reinforcement learning and simulation are necessary for training robots to perform non-human-like motions, as human data is insufficient for training beyond human capabilities.
🎯 Q: What does Boston Dynamics’ new humanoid demonstrate about motion? A: The robot demonstrates advanced symmetry, balance, and whole-body coordination, suggesting a shift towards robots inventing their own motion primitives unconstrained by human limitations.
🎮 Q: What are the limitations of simulation platforms for robot training? A: Platforms like Aubot’s Genie Sim 3.0 with NVIDIA Isaac SIM provide 10,000+ hours of synthetic data, but high-fidelity physics is still needed for accurate tactile feedback and locomotion.
⚠️ Q: Why do LLMs struggle with robot training scenarios? A: Edge cases occurring once in a million are critical for training, but LLMs struggle to generate these rare unpredictable scenarios, limiting their effectiveness in robot training.
Dexterity and Sensing.
🎯 Q: Can simple grippers match complex robotic hands? A: AI-driven dexterous hands can outperform highly capable robotic hands through extensive training, as demonstrated by Aloha project where simple paddle grippers performed complex tasks like tying knots.
👁️ Q: When is proprioception more effective than vision? A: Proprioception and touch sensing can be more effective than vision, as shown by DLR study where robotic arm with only joint torque sensors identified where a person was pushing, enabling tasks like writing.
🔍 Q: Why is sensor fusion crucial for robotics? A: Sensor fusion is crucial as demonstrated by personal experience where closing eyes improved performance due to misleading visual input, highlighting importance of combining different sensory inputs.
🤲 Q: What sensing layers do robotic hands need? A: Multi-layered sensing combining touch, proprioception, and joint sensing is necessary for tasks like feeling vibrations and detecting contact with threads, as vision alone has limitations.
🔩 Q: Is back-drivability a hardware or software property? A: Back-drivability is primarily a software property, not hardware, as demonstrated by worm gear drive in Shankai hand, which is very hard to back-drive mechanically.
Robot Safety.
⚠️ Q: What is the primary safety concern with robot motion design? A: Safety is a major concern when allowing robots to design their own motions or forms, as there are countless potentially unsafe combinations that need extensive training to address.
🚫 Q: Should you catch a falling humanoid robot? A: Never catch a falling robot; design robots to learn to fall safely and avoid catching them, as they can weigh 70kg and may flail unexpectedly due to software glitches.
📏 Q: What safe distance should robots maintain from humans? A: Robots should maintain a 2-meter safe distance from humans; if a person encroaches, the robot must move away or emit a loud warning signal to avoid collisions.
🔊 Q: How should robots warn humans of their approach? A: Robots should emit loud, attention-grabbing warning signals when approaching humans in urban environments, rather than annoying backup beeping used in cars.
🏭 Q: What should be prioritized over viral robot demos? A: Robots must be designed with safety and reliability as top priorities, focusing on serviceability over viral moments, to prevent accidents and ensure safe operation in real-world environments.
Surgical Robotics.
🏥 Q: When will surgical bots outperform human surgeons? A: Surgical bots could outperform human surgeons in 10–20 years, but teleoperation and human oversight will remain crucial, as no fully automated surgical procedures exist today.
⏳ Q: What will delay widespread adoption of surgical bots? A: Liability concerns, training requirements, and need for human-robot collaboration, especially with nervous child patients, will delay widespread adoption for at least 10 years.
🤖 Q: Will humanoid robots be optimal for surgery? A: 3D printer-like automation with fixed tools may be more suitable for certain surgeries than humanoid robots, despite perception that humanoids are most capable robots.
👨⚕️ Q: Why is human presence still critical in surgery? A: Human connection and trust in doctors are vital for patient cooperation, especially with children, and may be lost with fully automated surgical bots.
🖐️ Q: Can current humanoid hands perform surgery? A: Surgical bots will likely be teleoperated by humans for a long time, as no humanoid robot hand has yet demonstrated the dexterity and precision required for surgery.
💰 Q: How will advanced surgical bots be distributed? A: The first Optimus surgical bots that could outperform human surgeons will likely be limited in number (10,000) and expensive, raising questions about access and distribution of best surgical care.
## Key Insights.
Manufacturing and Design Trade-offs.
🔧 Boston Dynamics’ new Atlas robot uses only 2 unique actuators to minimize cost and complexity, with reliable rotary actuators replacing linear ones and enabling quick limb swapping in under 5 minutes for factory floor use.
⚙️ Reducing SKU count in actuators for mass production can lead to overactuation or underactuation in humanoid robots, as seen with a large actuator at the ankle needed for ankle roll motion but creating suboptimal reflected inertia.
🏭 Manufacturing scale impacts actuator design choices, with millions per year allowing more actuator types while thousands per year favors fewer types, leveraging Hyundai’s expertise in building manufacturing lines.
🔄 Boston Dynamics’ new Atlas incorporates manufacturability and serviceability considerations with common parts for both left and right limbs, enabling cost-effective production and simplified maintenance.
🦿 The new Atlas features a changed waist design and kinematics with individual actuators at knee and ankle, allowing for part reuse and cost reduction in manufacturing.
Mechanical Limitations and Failure Points.
⚠️ Parallel mechanisms like RSU at the waist can fail, lose torque transparency, and confuse actuators due to torque splitting between them, with linkages at the waist being a known weak point prone to failure.
✅
CES is where humanoid robots put on their best show.
Backflips, flawless motion, cinematic demos and bold promises.
But beneath the spectacle, a harder question remains:
Are humanoid robots actually improving or are the demos simply getting flashier?
In this episode of @overthehorizon, I’m joined by robotics experts Scott Walter, Gustav Andersson, and Mehrdad Farimani for a post-CES reality check on the state of humanoid robotics.
🚨We go beyond the hype to examine what recent CES demos really reveal about:
• The data bottleneck in humanoid training and why teleoperation still matters.
• Actuator strategies, SKUs, and the manufacturing trade-offs shaping robot design.
• Why spectacular demos can hide mechanical and safety limitations.
• The limits of simulation and synthetic data for real-world deployment.
• Whether humanoid robots are optimised for tasks or for perception.
• Why safety, reliability, and serviceability now matter more than viral moments.
‼️This is not a CES recap.
It’s a technical, grounded assessment of where humanoid robotics actually stands and where the industry may be misleading itself.
🔥If you care about real progress, not demo theatre, this conversation is for you.
#humanoidrobots #Robotics #CES #PhysicalAI #EmbodiedAI #AI #Automation #RoboticsEngineering #FutureOfWork #TechAnalysis