Arnesh Das, a student at Masterman High School, worked with us this summer through the Penn Engineering High School Internship Program (HIP). Today he presented his work at the HIP research symposium!

Alfred Gao

Sofia Padilla Regules

Elias Chavez

Yi Lu Zheng

Eliane Juang, Alfred Gao, Gabe Unger, Sofia Padilla Regules, Srijon Sarkar

Dongsheng’s thesis: Design, Performance Analysis and Motion Control of a Jet-Propelled Soft Robotics Platform

Monitoring underwater ecosystems is critical for assessing marine biodiversity and tracking the ongoing impacts of global climate change. Bio-inspired soft robots present an ideal solution for these environments, leveraging morphological mimicry, physical compliance, and low-acoustic locomotion to enable the non-disruptive observation of aquatic life. In this thesis, we investigate a squid-inspired, jet-propelled robotic platform, presenting contributions in its mechatronic design, performance analysis, and autonomous motion control.

Specifically, we developed a variable-volume, jet-propelled robot. The robot simulates the pulsatile dynamics of biological squids; its consistent kinematics and modular design enable it as a versatile testbed for studying complex fluid-structure interactions and validating motion control frameworks. By leveraging the system’s modularity, we adapt the robot to emulate the jetting mechanics of a biological salp and conducted an experimental analysis on the influence of unidirectional versus bidirectional flow regimes on the platform’s propulsive efficiency. Based on the experiment results, we formulated design guidelines to decide the selection between unidirectional and bidirectional flow regimes in jet-propelled aquatic systems. Finally, to achieve autonomous 2D planar locomotion, we integrated a steerable nozzle into the testbed architecture. Considering the highly nonlinear dynamics of the platform, we developed a Reinforcement Learning (RL) motion controller. This control policy was initially trained and validated within a custom dynamic simulation environment before being successfully deployed onto the physical hardware, demonstrating the efficacy of the closed-loop control framework.

Shivangi’s thesis: Modeling and Motion Planning for Robotic Systems with Networked Compliance

Physical compliance enters robotic systems either by design, to yield gracefully to disturbances, or by circumstance, as a property of the environment or task itself. Often this compliance is distributed across many interacting elements, and how those elements are connected determines whether their combined effect on the robot’s configuration can be resolved locally or as a coupled system. In this talk, I will discuss how to model and plan over two such systems: a soft manipulator arm with tunable stiffness elements, and a physically connected team of mobile robots that cooperatively traverse deformable, slip-prone terrain. We use a graph-theoretic model of the connected compliant elements in each system to capture how motion is coupled to the underlying forces. Leveraging its model, the soft arm motion planner adjusts internal stiffness to redistribute forces resulting in a target shape, while for the connected robot team, where terrain compliance is fixed, the planner reasons over modeled interaction forces to select robot actions that guide the team toward a goal. In each case, the same underlying model supports planning across a range of network topologies and terrain conditions.

https://curf.upenn.edu/about-us/student-news/More-Than-Just-Robotics-Research

Jeffrey Oduman (CS BSE ’28) has been working in our lab on gradient descent of 3D Dubins paths as part of the Kinegami project. His work was supported by the Penn Undergraduate Research Mentoring Program from the Center for Undergraduate Research and Fellowships (CURF). His reflections on this experience were recently featured on the CURF’s blog!