Introduction

Simulation Methods

Puncher Robot

Team Gait Keepers: Jack Clark, Steven Jorgensen, Isaac Fenta, Shannen Kizilski 2.S994/2.S997: Biomimetics, Biomechanics, and Bio-inspired Robotics

Massachusetts Institute of Technology

Simulation Results Experimental Results

Discussion

Conclusion

Experimental Methods

Athletes of many sports unconsciously demonstrate sequential activation of their joints when performing motions such as throwing or hitting. The goal of this experiment is to study the effect of sequential joint activation on output force. Using a scaled model of a human arm, simulation and optimization were performed to determine the ideal activation timings for each joint during a lateral punch. The optimized timings were programmed into a physical model and output force was measured with a force sensor attached to the end-effector.

Simulation model extracted from human arm and torso configuration, simplified to planar geometry Torso

Elbow

Fist Shoulder

Optimization

Objective: Find activation and deactivation timings of each motor to maximize force output at fist

Variables: Activation and deactivation time for each motor

Constraints:

• Physical limitations to range of motion

• Start Time ≤ Activation time ≤ Deactivation time

• End-Effector location is on the wall at end time

Torso motor

Force sensor

Shoulder motor

Elbow motor

Elbow joint

Hardware • 3D printed torso and arm links • Belt system to drive forearm link • Pololu 19:1 metal gearmotors

Circuitry • mbed microcontroller • 3 VNH5019 Motor Drivers

Force Measurement 100 N force sensor • Divide output voltage before

sending to mbed • Calibrated sensor with known

force inputs Impact Acceleration • Record high speed video of fist

impacting object of known mass • Use tracking software to find

acceleration

Simulated Punch Implementation

Follow a desired trajectory while applying desired torque at proper activation times • Generate desired joint positions

obtained from simulation results • Use PD control at each joint to

achieve desired positions • Turn desired motor torque on or off

using 1 kHz ticker and timings obtained from simulation

• Implementation worked, but has issues matching with simulations

0.00

0.05

0.10

0.15

0.20

0.00 0.05 0.10 0.15 0.20

Y-Po

siti

on

X-Position

Simulation Experiment

Due to the gradient approach in finding optimal force, the optimization tended to vary only a single joint time parameter. A slight change in the initial condition or initial joint timing guess resulted in weak forces or irregular punch motions. Further, if the joints are not sequential, the forces are even weaker. This shows how sequential joint activation is crucial to optimal force output.

Initial Torso Angle

0 -π/3 -2π/5

Output Impulse

17Ns 30Ns 39Ns

Joint 1 Deactivation

1.0000s 0.9973s 1.0559s

Impact Time 0.5663s 1.0514s 1.3048s

Fig. 1: Initial Torso Angle: 0 Initial Upper-Arm Angle: 0 Initial Forearm Angle: π/3 Blue line on right side represents a physical wall. When simulated robot’s fist hits the wall, an output impulse is recorded.

Optimization • Very sensitive to initial conditions and

initial activation and deactivation timing guesses

• Reasonable initial guesses get trapped in local minima

• Optimization code returns similar activation and deactivation times

• A negative activation torque at elbow joint is necessary for fist-wall contact

Effect of changing Joint 1 initial position

• High Rotational Energies correspond to higher impact forces • Initial conditions and initial guesses significantly vary the

performance of the punch as well as the required joint activation timing for an optimal punch.

• Future Work: Vary wall distance to observe changes in optimal trajectory.

When the simulated punch was implemented in the robot, trajectory control caused robot to deviate from the commanded path. Additionally friction in the elbow joint causes a mismatch between the simulation’s optimized force output and the experimental result.

-1

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

0 0.5 1 1.5 2 2.5 3 3.5

Rad

ian

s

Time

Trajectory Tracking

Theta 1

Theta2

Theta 3

Desired Theta

0

0.5

1

1.5

2

2.5

0 0.5 1 1.5 2 2.5 3 3.5

Forc

e (

N)

Time

Force Output