Researchers from UC Berkeley’s Biomimetic Millisystems Lab have been busy developing their Salto jumping robot since its debut in 2016. Back then, the robot was capable of jumping at great heights, but had orientation issues and could only complete two jumps in a row before crashing.

The researchers have since solved the orientation issues with the Salto-1P (Saltatorial Locomotion on Terrain Obstacles), which can now jump higher, longer, faster, and with more repetitions than the previous version.

The original Salto relied on a rotating inertial tail to control its pitch while jumping, and it worked well, but for only one plane, making it difficult to control. The Salto-1P has been upgraded so that it can orient itself in mid-air by still using the same inertial tail, but with the added support of a pair of thrusters to maintain stability.

Salto is capable of jumping to a height of 4.1-feet by using a small motor, elastic actuator and a tail-positioned gearbox that propels the robot’s single leg at a velocity of 1.83 m/s. Once in the air, it can maintain position or pitch, roll and yaw in any direction using the thrusters (Cheerson CX-10 quadcopter propeller blades).

The Salto-1P control block diagram shows how the robot is controlled while in motion.

Control of the robot is done with an onboard ImageProc 2.5 robot control board, along with a BLDC motor-driver, while the tail and the thrusters are driven by H-bridges. To maintain stability while jumping, the ImageProc uses telemetry data from the motor-driver and a 6-axis IMU sensor, allowing it to achieve and sustain jump repetitions.

The software that controls the show is derived from an algorithm created by Marc Raibert for his 3D One-Leg Hopper he designed in 1984, and although it works nearly the same for the Salto-1P, it needed to be modified to fit the robot’s lightweight specs (the Hopper weighed 170-times more than the Salto’s 0.98 kg).

As far as the future goes for the Salto-1P, the researchers plan to continue its development to achieve better control interaction with different obstacles and terrain along with landing control and strategies that would allow the robot to jump off walls more than once.

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