
Robots struggle with endurance. Feeding them could help
Earlier this year, a robot completed a half-marathon in Beijing in just under 2 hours and 40 minutes. That's slower than the human winner, who clocked in at just over an hour—but it's still a remarkable feat. Many recreational runners would be proud of that time. The robot kept its pace for more than 13 miles (21 kilometers).
But it didn't do so on a single charge. Along the way, the robot had to stop and have its batteries swapped three times. That detail, while easy to overlook, speaks volumes about a deeper challenge in robotics: energy.
Modern robots can move with incredible agility, mimicking animal locomotion and executing complex tasks with mechanical precision. In many ways, they rival biology in coordination and efficiency. But when it comes to endurance, robots still fall short. They don't tire from exertion—they simply run out of power.
As a robotics researcher focused on energy systems, I study this challenge closely. How can researchers give robots the staying power of living creatures—and why are we still so far from that goal? Though most robotics research into the energy problem has focused on better batteries, there is another possibility: Build robots that eat.
Robots move well but run out of steam
Modern robots are remarkably good at moving. Thanks to decades of research in biomechanics, motor control, and actuation, machines such as Boston Dynamics' Spot and Atlas can walk, run, and climb with an agility that once seemed out of reach. In some cases, their motors are even more efficient than animal muscles.
But endurance is another matter. Spot, for example, can operate for just 90 minutes on a full charge. After that, it needs nearly an hour to recharge. These runtimes are a far cry from the eight- to 12-hour shifts expected of human workers—or the multiday endurance of sled dogs.
The issue isn't how robots move—it's how they store energy. Most mobile robots today use lithium-ion batteries, the same type found in smartphones and electric cars. These batteries are reliable and widely available, but their performance improves at a slow pace: Each year new lithium-ion batteries are about 7% better than the previous generation. At that rate, it would take a full decade to merely double a robot's runtime.
Animals store energy in fat, which is extraordinarily energy dense: nearly 9 kilowatt-hours per kilogram. That's about 68 kWh total in a sled dog, similar to the energy in a fully charged Tesla Model 3. Lithium-ion batteries, by contrast, store just a fraction of that, about 0.25 kilowatt-hours per kilogram. Even with highly efficient motors, a robot like Spot would need a battery dozens of times more powerful than today's to match the endurance of a sled dog.
And recharging isn't always an option. In disaster zones or remote fields, or on long-duration missions, a wall outlet or a spare battery might be nowhere in sight.
In some cases, robot designers can add more batteries. But more batteries mean more weight, which increases the energy required to move. In highly mobile robots, there's a careful balance between payload, performance, and endurance. For Spot, for example, the battery already makes up 16% of its weight.
Some robots have used solar panels, and in theory these could extend runtime, especially for low-power tasks or in bright, sunny environments. But in practice, solar power delivers very little power relative to what mobile robots need to walk, run, or fly at practical speeds. That's why energy harvesting like solar panels remains a niche solution today, better suited for stationary or ultra-low-power robots.
Why it matters
These aren't just technical limitations. They define what robots can do.
A rescue robot with a 45-minute battery might not last long enough to complete a search. A farm robot that pauses to recharge every hour can't harvest crops in time. Even in warehouses or hospitals, short runtimes add complexity and cost.
If robots are to play meaningful roles in society assisting the elderly, exploring hazardous environments, and working alongside humans, they need the endurance to stay active for hours, not minutes.
New battery chemistries such as lithium-sulfur and metal-air offer a more promising path forward. These systems have much higher theoretical energy densities than today's lithium-ion cells. Some approach levels seen in animal fat. When paired with actuators that efficiently convert electrical energy from the battery to mechanical work, they could enable robots to match or even exceed the endurance of animals with low body fat. But even these next-generation batteries have limitations. Many are difficult to recharge, degrade over time, or face engineering hurdles in real-world systems.
Fast charging can help reduce downtime. Some emerging batteries can recharge in minutes rather than hours. But there are trade-offs. Fast charging strains battery life, increases heat, and often requires heavy, high-power charging infrastructure. Even with improvements, a fast-charging robot still needs to stop frequently. In environments without access to grid power, this doesn't solve the core problem of limited onboard energy. That's why researchers are exploring alternatives such as 'refueling' robots with metal or chemical fuels—much like animals eat—to bypass the limits of electrical charging altogether.
An alternative: Robotic metabolism
In nature, animals don't recharge; they eat. Food is converted into energy through digestion, circulation, and respiration. Fat stores that energy, blood moves it, and muscles use it. Future robots could follow a similar blueprint with synthetic metabolisms.
Some researchers are building systems that let robots 'digest' metal or chemical fuels and breathe oxygen. For example, synthetic stomach-like chemical reactors could convert high-energy materials such as aluminum into electricity.
This builds on the many advances in robot autonomy, where robots can sense objects in a room and navigate to pick them up, but here they would be picking up energy sources.
Other researchers are developing fluid-based energy systems that circulate like blood. One early example, a robotic fish, tripled its energy density by using a multifunctional fluid instead of a standard lithium-ion battery. That single design shift delivered the equivalent of 16 years of battery improvements, not through new chemistry but through a more bioinspired approach. These systems could allow robots to operate for much longer stretches of time, drawing energy from materials that store far more energy than today's batteries.
In animals, the energy system does more than just provide energy. Blood helps regulate temperature, deliver hormones, fight infections, and repair wounds. Synthetic metabolisms could do the same. Future robots might manage heat using circulating fluids or might heal themselves using stored or digested materials. Instead of a central battery pack, energy could be stored throughout the body in limbs, joints and soft, tissue-like components.
This approach could lead to machines that aren't just longer-lasting but are more adaptable, resilient, and lifelike.
The bottom line
Today's robots can leap and sprint like animals, but they can't go the distance.
Their bodies are fast and their minds are improving, but their energy systems haven't caught up. If robots are going to work alongside humans in meaningful ways, we'll need to give them more than intelligence and agility. We'll need to give them endurance.

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
36 minutes ago
- Yahoo
Nvidia Stock (NVDA) Preserves Pack Leader Status Following Q1
Nvidia (NVDA) once again proved to the markets, after reporting its Q1 earnings, that it remains the undisputed leader powering the global AI revolution, driven by relentless demand for its chips, even amid ongoing geopolitical and trade headwinds. Easily unpack a company's performance with TipRanks' new KPI Data for smart investment decisions Receive undervalued, market resilient stocks right to your inbox with TipRanks' Smart Value Newsletter Beyond beating all key metrics (excluding one-off events) and offering guidance that resonated well with investors, Nvidia stock experienced a strong post-earnings surge, even if the momentum cooled slightly in the days that followed. That said, there's arguably still a missing spark needed to fully reignite the stock's momentum heading into 2025. However, considering the broader growth story, Nvidia continues to trade at a very attractive valuation—one that could deliver meaningful alpha over the long term. Short- to mid-term bumps, especially tied to macro risks in China, are worth monitoring but don't alter the core thesis. Given the company's strong execution and still-intact fundamentals, I continue to rate NVDA as a Buy. As I pointed out in a previous article, for Nvidia stock to perform well after its Q1 Fiscal 2026 results, it wouldn't be enough to simply beat estimates—it needed to crush them and deliver guidance that topped market expectations. And that's precisely what Nvidia did. The company reported revenue of $44 billion (as shown in the chart below), beating its own guidance of $43 billion—a massive 69% increase year-over-year. Gross margins, which had been a point of concern during the early stages of Blackwell's rollout, came in at 71.3% (excluding the H20 charge, a financial write-off tied to its China-specific H20 GPUs). That's also above the guided range of 70.6% to 71%. Even more impressive was the Q2 guidance. Nvidia is projecting $45 billion in revenue, with a margin of plus or minus 2%. At the high end, that's $45.9 billion—above the ~$45.5 billion consensus estimate leading into earnings day. Margins are expected to rise again, landing between 71.8% and 72.0%, with a margin of error of approximately 50 basis points. At the top of that range, it suggests another round of margin expansion, which is exactly what investors wanted to hear. The company continues to state that once Blackwell production is fully ramped, margins could move into the 70–80% range over the next few quarters. This stronger-than-expected performance, along with the recovery in margins, led to long-term EPS estimates getting bumped up by around 9% starting in FY2029. Revenue projections for those years were also revised higher by roughly 8%. Not surprisingly, Nvidia shares jumped more than 5% in after-hours trading following the earnings release, although the stock mostly leveled off in the sessions since. In my view, the muted post-earnings reaction is actually a positive sign—it shows the market didn't see enough red flags to justify a selloff in Nvidia stock. However, bears argue that even with revenue jumping nearly 70% year-over-year, signs of fatigue in the growth story are evident, with sequential growth of just 12% potentially indicating that Nvidia's explosive momentum is entering a more seasonal or plateauing phase. For a company priced for hypergrowth, this kind of quarter-over-quarter slowdown can be an early warning signal. And it's not just about the numbers—geopolitical and regulatory pressures are starting to have real consequences. The U.S. export restrictions on AI chips like the H20 led to a $4.5 billion write-down and forced Nvidia to walk away from an estimated $15 billion in potential sales to China. That's not just a short-term financial hit—it also opens the door for competitors like Huawei to gain ground, especially as they accelerate domestic chip development. Although analysts have raised long-term estimates following Q1, there remains a genuine possibility that Nvidia's global dominance could face challenges over time, particularly if policy pressures persist. When factoring in the impact of the H20 write-off, Q1 would have been the first quarter since the AI boom began in which Nvidia did not achieve sequential growth. And for a stock valued for perfection, even a modest slowdown can pose a valuation risk. To me, the bigger issue here is that this goes beyond Nvidia—it's about the strategic direction of U.S. tech leadership. As CEO, Jensen Huang has warned that if the U.S. continues down this restrictive path without a more balanced strategy, it may ultimately strengthen Huawei and erode America's edge in AI. That's the kind of long-term headwind that bears are likely to latch onto as the growth narrative gets more complicated. But setting the macro risks aside, Nvidia's bull case remains intact after Q1, especially when considering its growth. The company continues to stand out as a GARP (growth at a reasonable price) opportunity. Currently, Nvidia trades at 31.6x forward earnings, with a consensus growth rate of 29% CAGR over the next three to five years. This results in a PEG ratio of just 1x—virtually identical to Advanced Micro Devices (AMD), despite AMD's significantly slower growth outlook, and significantly lower than most of the other Magnificent 7 names. Of course, for that valuation to hold up, Nvidia's growth trajectory needs to remain clean and strong. But honestly, it's hard to think of another company with Nvidia's size and scale, this level of fundamental quality, and such massive exposure to secular tailwinds like AI, trading at such an attractive growth-adjusted valuation. Among the 40 analysts who've covered NVDA in the past three months, there's hardly any room for doubt: 35 rate the stock as a Buy, while only four suggest Hold. Not a single analyst rates NVDA stock as a Sell. Currently, NVDA's average stock price target is $173.57, implying a potential upside of 22% from the current share price. Setting aside one-off events, Nvidia left the bears with almost nothing to complain about—crushing its own guidance and delivering a Q2 forecast that dispels doubts about how quickly gross margins are recovering. While risks like evolving U.S. sanctions on China, Nvidia's ability to maintain its presence in that market, and rising local competition are worth keeping an eye on, they don't outweigh the current risk-reward of going long, especially given the company's strong growth trajectory. Disclaimer & DisclosureReport an Issue Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
41 minutes ago
- Yahoo
Why Pony AI Inc. (PONY) Crashed On Wednesday
We recently published a list of . In this article, we are going to take a look at where Pony AI Inc. (NASDAQ:PONY) stands against other worst-performing stocks on Wednesday. Pony AI Inc. (NASDAQ:PONY) dropped its share prices by 5.06 percent to finish at $13.14 apiece as investors disposed of shares amid the risks of the faltering US-China trade talks and renewed calls from other states to delist Chinese firms from the stock exchanges. Following the two countries' 90-day tariff truce, US President Donald Trump expressed his frustration with China on Wednesday, saying that Chinese President Xi Jinping is 'very tough and extremely hard to make a deal with.' A close-up of a digital cloud, signifying the expansive reach of the software-as-a-service solution. Trump's social media post casted doubts over an expected potential phone call between the two leaders this week, with fears spilling over to stocks of Chinese companies, including Pony AI Inc. (NASDAQ:PONY). Further triggering concerns were mounting calls from US states' comptrollers to delist Chinese companies. In a newly issued statement, Indiana Comptroller Elise Nieshalla said that there is a growing risk posed by China-based companies due to widespread failures to meet US transparency, accounting, and standards. 'As stewards of invested public funds, we have a responsibility to protect our beneficiaries from foreign entities to seek to exploit our capital markets while evading accountability,' she said. READ NEXT: 20 Best AI Stocks To Buy Now and 30 Best Stocks to Buy Now According to Billionaires. Disclosure: None. This article is originally published at Insider Monkey. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data


The Verge
2 hours ago
- The Verge
iFixit says the Switch 2 is even harder to repair than the original
After retroactively lowering the original Nintendo Switch's repairability score from an 8 out of 10 to just 4 out of 10 to reflect 2025 standards, iFixit has found the Switch 2 to be even harder to fix. Following its full teardown of the new console, iFixit is giving the Switch 2 a 3 out of 10 repairability score thanks, in part, to a battery that's once again 'glued in with powerful adhesive' and flash storage modules and USB-C ports that are soldered to the main board. Nintendo continues to rely on the tri-point screws the company has been using to assemble its consoles and handhelds for decades, and on the Switch 2, many are hidden behind stickers that get damaged in the process of removing them to access the screws. The company has never released repair parts or manuals for the original Switch, and there are currently none available for the Switch 2, so you'll need third-party alternatives to reassemble the console. Components like the headphone jack, speakers, microphone, and microSD reader on the Switch 2 are easy to remove. As are buttons that are soldered to breakout boards, and the console's cooling fan that's held in place by three screws. But iFixit describes removing the Switch 2's battery as an 'absolute mission' and 'just as bad as the original Switch.' Lots of isopropyl alcohol and a 'whole set of pry tools' were needed to remove it, and in the process the foam Nintendo glued to the battery was left disintegrated making a future battery swap a difficult and messy endeavor. The Switch 2's gamecard reader, which was modular and relatively easy to remove and replace in the original Switch and Switch OLED models, is now soldered to the console's mainboard as it is on Switch Lite. iFixit also found three different types of thermal paste used in the Switch 2 which in the original Switch would solidify over time making it hard to remove and less effective at preventing the console from overheating. Even the new Joy-Cons on the Switch 2 are harder to disassemble, which is problematic because the joysticks are using the same potentiometer technology as the original Joy-Cons that rely on a resistive material that can wear away over time. That's one of the causes of the original Switch's notorious joystick drift issue and this time around it's going to be even harder to do repairs or replace the sticks altogether with Hall effect or TMR alternatives.