We used peanuts and a climbing wall to learn how squirrels judge their jumps so well – and how their skills might inspire more agile robots.

Tree squirrels are the Olympic divers of the rodent world, gracefully leaping among branches and structures high above the ground. And as with human divers, a squirrel’s success in this competition requires both physical strength and mental adaptability.

The Jacobs lab is studying cognition in free-roaming fox squirrels on the Berkeley campus. Two species – the eastern gray squirrel (Sciurus carolinensis) and the fox squirrel (black squirrel) – thrive on campus landscapes and voluntarily participate in our behavioral experiments. They are also masters of two-dimensional and three-dimensional spatial orientation – using sensory cues to move through space.

In a recently published study, we show that squirrels jump and land without falling by making trade-offs between the distance they have to travel and the elasticity of their take-off perch. This research provides new insight into the roles of decision making, learning, and behavior in challenging environments that we share with human movement researchers and engineers. Right now, there isn’t a robot as agile as a squirrel, and none that can learn or make decisions on dynamic tasks in complex environments – but our research suggests the types of abilities these robots have. would need.

Thinking on the go

While the life of a squirrel may seem simple to human observers – climbing, eating, sleeping, snoozing – it involves finely tuned cognitive skills. Squirrels are specialized seed dispersers: they harvest their winter stores of nuts and acorns for six to eight weeks in the fall, bury each nut separately, and rely on spatial memory to retrieve them, sometimes months later. .

We know that squirrels organize their caches hierarchically. When given five species of nuts in random order, the Berkeley squirrels buried the nuts in clusters according to the species. Because larger nuts contain more calories, squirrels invest more in them, transporting them to safer places and spacing out their hiding places further.

We also found that a squirrel assesses the value of a nut by shaking its head with the nut in its mouth, just as a human might pull a pencil in its hand to assess its weight. And we know that they create their cache cards based on factors such as the scarcity of food during this season, the amount of nuts already hidden, and the risk of being observed hiding by other squirrels.

Along with observational studies, we also evaluated how squirrels perform abstract spatial tasks. For example, we measured how able they are to inhibit a split to a memorized food location – as part of an international study on the evolution of self-control. In another experiment, we placed squirrels in a vertical maze that mimicked the branching decisions they faced when navigating through trees to see how they returned to places they remember.

We also found that as squirrels solved a tabletop memory puzzle, their cognitive flexibility peaked during the intense period of storing their winter food. This explains why the Berkeley squirrels are able to switch between types of cue more easily during caching season.

To take some fresh air

Our new study brought together squirrel psychologists and comparative biomechanists to question whether squirrel cognitive decision-making extends to dynamic changes in locomotion – the infamous squirrel hopping. How do squirrels’ perceived abilities of their bodies and their assumptions about the stability of the environment shape their decisions about movement?

Robert Full of the PolyPEDAL lab is renowned for his studies that extract fundamental design principles through locomotion experiments in species with unique specializations for movement, from crabs to cockroaches to jumping lizards. Graduate students Nathaniel Hunt, who is trained in biomechanics, and Judy Jinn, who is trained in animal cognition, took on the challenge of evaluating how a jumping squirrel might respond to sudden changes in the location and flexibility of experimental branches.

To study this question in wild squirrels, we designed a magnetic climbing wall that could be mounted on wheels and deployed to the famous Berkeley eucalyptus grove to meet the squirrels on their own grass. We brought super-fast cameras and peanuts to persuade the squirrels to patiently wait their turn on the wall.

Our goal was to persuade the squirrels to take off from a flexible springboard attached to the climbing wall and jump to a fixed perch protruding from the wall that contained a shelled nut reward. And once again, the squirrels surprised us with their acrobatics and innovation.

By increasing the springboard’s elasticity and the distance between it and the goal, we could simulate the challenge a squirrel faces when running through branches of trees that vary in size, shape, and flexibility. Squirrels jumping over a hole must decide where to take off based on a trade-off between limb flexibility and the size of the gap.

We found that the squirrels ran further along a steep branch so they had a shorter and easier jump. On the other hand, they took off a few steps from flexible branches, risking a longer jump.

Using three different branches in flexibility, we guessed the position of their take-off assuming an equal risk of jumping from an unstable branch and a jump distance. We were wrong: Our model showed that squirrels cared six times more about a stable take-off position than how far they had to jump.

Then squirrels jumped off a very rigid platform. Unbeknownst to the squirrels, we then substituted an identical-looking platform that was three times more flexible. From our high-speed video, we calculated how far the center of the squirrel’s body was from the landing perch. This allowed us to determine the landing error – how far the center of the squirrel’s body landed from the perch of the goal. The squirrels quickly learned to jump from the very bent branch which they thought was stiff and could land a successful landing in just five tries.

When we increased the bet even more by increasing the height and distance to the goal perch, the squirrels surprised us. They immediately adopted a new solution: parkour, which literally bounces off the climbing wall to adjust its speed and achieve a graceful landing. Once again, we’ve discovered the remarkable agility that allows squirrels to evade predators in one of nature’s toughest environments, the canopy of trees.

Millions of people have seen squirrels solve and loot “squirrel-proof” bird feeders, either in their backyards or in documentaries and viral videos. Like Olympic divers, squirrels must be flexible both physically and cognitively to be successful, quickly correcting mistakes on the fly and innovating new movements.

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With the funding this project attracted, we joined a team of roboticists, neuroscientists, materials scientists and mathematicians to extract the design principles of squirrel jumps and landings. Our team is even seeking to better understand how the brain works by studying the planning of jumps in laboratory rats.

Our analysis of the remarkable feats of squirrels may help us understand how to help humans with walking or gripping disabilities. Additionally, with our interdisciplinary team of biologists and engineers, we are trying to create new materials for the smartest, most agile robot ever built – one that can aid search and rescue efforts and quickly detect risks. catastrophic environmental factors, such as toxic chemicals. released.

A future vision of our efforts? First responder robotic squirrels, endowed with the physical and cognitive stamina and flexibility of a squirrel in a bird feeder.

Judy Jinn, who participated in this study as a graduate student, is a quantitative UX researcher at Facebook.