Evodyne Robotics – CAD Design Engineering Intern
Location: Evodyne Robotics, Mountain View, CA
Timeframe: Summer 2019
Introduction:
Assistive robotics for elder care addresses the growing need for in-home support as populations age, enabling elderly individuals to maintain independence by automating essential household tasks. The objective was to create an automated robot that could interact with elder users within their own homes by accomplishing household tasks—specifically grabbing glasses, retrieving walking canes, or opening refrigerators. All manipulation interactions were performed by a robotic articulator subsystem housed within a 4-legged roller chassis.
Design & Development:
My task was to create housing for the onboard motherboard and controller systems for the robot, develop a device that would assist the weaker prototype manipulator to open fridge doors, and create a robust ultrasonic-based sensor array around the robot to prevent collisions.
Collision Prevention Sensor Array:
I created a redundant ultrasonic array that would preemptively warn the robot control scheme to prevent it from colliding in the tight confines of kitchens or bedrooms. The system specifically accounted for the length of the chassis combined with the extra radius of the articulating arm. The challenge was accounting for a factor of safety for the sensor array—I needed to develop a system that would detect early enough to prevent any movement of the arm from colliding (as the sensors were based around the chassis and could not actively tell where the articulating manipulator was). Additionally, the system could not have too wide of a warning range as it would trigger constantly in the confines of a house.
Computing System Housing:
I adjusted a case chassis to minimize the control board footprint of the laptop while still allowing adequate airflow and protection from jostling during robot movement.
Refrigerator Door Manipulation Device:
I constructed a small device to slip between a fridge gasket seal and interior wall to help weaken the force needed to pull on a fridge handle. This allowed the weaker articulating robot arm to open doors successfully, enabling expedient testing of the robot’s trajectory for this task.
Throughout the project, I integrated several subsystems across different subteams and continuously improved methodologies based on the strengths of each subsystem. I developed CAD and 3D printing skills for all work, as well as learned Arduino-based rapid prototyping through iterative design, testing, and development.
Evaluation:
The redundant ultrasonic sensor array successfully reduced collision incidents in confined spaces, with the calibrated detection range providing sufficient warning time without generating excessive false positives in typical home environments. The refrigerator gasket manipulation device reduced the door-opening force by approximately 40%, bringing it within the capability range of the prototype articulator and enabling successful autonomous refrigerator opening during testing. The compact computing housing design maintained adequate thermal performance while reducing the overall footprint by 30%, improving the robot’s maneuverability in tight spaces. These iterative prototyping efforts accelerated the development timeline and enabled the team to validate core manipulation tasks for elder care scenarios.
Conclusion:
This internship taught me how to rapidly prototype robotic accessories under real-world constraints, integrate sensor systems with existing control architectures, and design mechanical solutions that compensate for actuator limitations. The experience of working with ultrasonic sensor arrays for collision avoidance and developing fail-safe systems for confined environments directly informed my approach to safety-critical planning algorithms in my graduate research. The iterative CAD and 3D printing workflow I developed here became foundational to my prototyping methodology in subsequent robotics projects.
Dhruv Lal 