Objectives

LOCOMORPH was driven by a set of clearly defined scientific and technical objectives, designed to advance both the theoretical understanding and practical application of morphological computation in robotics.

Scientific Objectives

• Quantify morphological computation — Develop formal, information-theoretic measures that capture the extent to which a robot's physical body contributes to locomotion control, enabling principled comparison between body designs
• Identify biological principles — Extract the key biomechanical features that enable animals to achieve robust locomotion across varied terrain, and translate these into engineering design rules
• Understand body-brain coupling — Characterize the interaction between neural control and physical body dynamics, determining the optimal division of labor for different locomotion tasks
• Model developmental morphology — Investigate whether and how robots can benefit from changing their own body structure over their operational lifetime, analogous to biological growth and adaptation

Technical Objectives

• Build reconfigurable robot platforms — Design and construct modular legged robots whose limb geometry, joint properties, and material compliance can be quickly reconfigured for systematic experimentation
• Develop co-optimization methods — Create algorithms that simultaneously optimize a robot's body morphology and its locomotion controller, rather than treating them as separate design problems
• Create high-fidelity simulators — Build simulation environments that accurately model soft-body dynamics, ground contact, and material deformation, enabling large-scale morphological search
• Demonstrate terrain adaptability — Show that morphologically optimized robots can traverse challenging terrain types (gravel, slopes, obstacles) that defeat conventionally designed machines
• Release open-source tools — Make the modular robotics platform, simulation tools, and learning algorithms available to the broader research community

Impact Goals

Beyond the immediate research outputs, LOCOMORPH aimed to shift how the robotics community thinks about body design. The traditional approach — design a rigid body, then program a controller to compensate for its limitations — is deeply ingrained. LOCOMORPH's goal was to demonstrate a viable alternative: design the body and controller as an integrated system, where the body actively participates in the control process.

This shift in perspective has practical implications. Robots with well-designed morphologies are simpler to control, more energy-efficient, more robust to disturbances, and cheaper to build because they require less powerful actuators and computers. These advantages matter especially for robots intended to operate outside the lab — in disaster zones, agricultural fields, underwater environments, and other unstructured settings where robustness and efficiency are critical.