Summary of Key Points
Recent incidents where robots suddenly “fall down” have drawn attention, revealing shortcomings in current robot technology regarding environmental adaptation and body control. The phenomenon that it is more difficult for robots to “get up on their own” than to outrun Usain Bolt illustrates the complex challenges of embodied intelligence. Unlike simply increasing speed, robots need to perform multiple tasks simultaneously, such as perception, decision-making, and body coordination, which significantly increases the difficulty. This has also sparked discussions about whether capital is chasing a bubble. Although the robotics industry is seen as a future trend, there are many technical hurdles to overcome, and there is a need to be cautious of the risk of overhyping concepts rather than genuine breakthroughs.
1. Why do robots fall down suddenly? It’s not just about instability
Robot falls are not random; they often result from a breakdown in the “perception-decision-execution” chain:
- Sensor failures: Robots rely on cameras and lidar to perceive their environment. If the ground suddenly has wet spots or small stones (such as after cleaning), the sensors may not detect them in time, causing the robot to slip, just as a person might slip on a banana peel.
- Slow algorithm response: When faced with unexpected situations (e.g., a sudden collision), algorithms need to instantly calculate how to adjust the robot’s balance. If the algorithm’s processing speed is too slow, the robot loses balance.
- Weak hardware: Joints, motors, or hydraulic systems that malfunction or lack sufficient power (e.g., due to wear and tear after prolonged use) can cause the robot to lose support suddenly.
- Complex environment: Surfaces that are easy for humans to navigate (e.g., uneven or inclined ground) can be dangerous for robots. For example, in outdoor grass, changes in grass height and softness can lead to misjudgments in the robot’s movement.
In short, robots are still like babies learning to walk; they are prone to falling even with minor obstacles.
2. Why is it harder for robots to get up on their own than to outrun Bolt? It’s a test of overall coordination
Outrunning Bolt requires optimizing a single action (running), such as increasing leg power or stride frequency. However, getting up on one’s own is a completely different task that involves three major challenges:
- Understanding the cause of the fall: The robot must use sensors to determine its position (lying on its side, back, or face down) and the surrounding environment (whether there are obstacles).
- Deciding the order of actions: For example, when lying on its back, the robot needs to decide whether to lift its head first or its arms, and how much force to use to avoid falling again. This requires fast algorithmic planning.
- Coordinating all muscles: While humans coordinate their movements naturally, each robot joint needs precise control. For instance, the Boston Dynamics Atlas robot must adjust the angles and forces of more than 20 joints simultaneously; even a slight mistake can lead to failure.
To put it simply, outrunning Bolt is like training for a 100-meter sprint, while getting up on one’s own is like solving a complex mathematical problem that requires the coordination of the entire body. The difficulty levels are completely different.
3. Embodied intelligence is the key, but breakthroughs are slow to come
The so-called “embodied intelligence” means that robots should not only be able to think but also interact with their environment using their bodies, just as humans use their senses and limbs. However, this technology is still in its early stages:
- Simulating human behavior is difficult: It takes infants 6–8 months to learn to crawl, thanks to countless attempts and physical feedback. Robots need massive training data and real-time physical feedback systems to replicate this process.
- Lack of versatility: Current robots are trained in ideal laboratory conditions (flat, obstacle-free surfaces). In different environments (e.g., sand or stairs), they may fail to function properly.
- High cost: Robots that can get up on their own (like the Atlas) are extremely expensive, making them unaffordable for most companies, let alone for widespread commercial use.
Embodied intelligence is the future direction, but there is still a long way to go before robots become as agile as humans.
4. Capital’s enthusiasm: Real demand or a bubble?
The robotics industry has indeed seen significant interest, with record amounts of funding in both industrial and service robots. However, this enthusiasm may also hide potential bubbles:
- Overemphasis on concepts: Some companies claim to have made breakthroughs by creating robots that can get up, but practical applications (e.g., in homes or healthcare) are still far from mature.
- Unclear profit models: Many robotics companies rely on government subsidies or funding; profitable businesses (e.g., industrial robots used in welding) account for a small portion of their revenue.
- Unresolved technical challenges: Without solving core issues like autonomous movement and environmental adaptation, robots cannot become widely used in daily life. If capital only focuses on trendy topics rather than research and development, the industry may end up in a similar situation to shared bicycles.
However, it’s not entirely negative. Robots are indeed essential for future needs (e.g., elderly care and more flexible industrial applications). As long as companies focus on solving technical problems, they can create valuable products.
In conclusion, robot falls are not minor issues; they reflect underlying technical challenges. If capital is invested in genuine technological advancements, it’s promising. If it’s just about hyping concepts, caution is needed.