Robotic Systems Overview

Principles

Definition

Robotic systems is the interdisciplinary research field concerned with the design, construction, operation, and application of robots, investigating the integration of mechanical engineering, electronics, computer science, and artificial intelligence to create autonomous or semi-autonomous machines capable of performing tasks in diverse environments.

Ontological type

Core Subfields

System Architecture

Sensing and Perception

Key developments

Key Figures

Perception-Integrated Robust Control era

Oussama Khatib [1] of Stanford University [3] emerges as a central figure in perception-integrated robust control during the 1983-1996 era. Khatib [1]'s Real-Time Obstacle Avoidance for Manipulators and Mobile Robots paper [6] demonstrated the real-time integration of perceptual sensors into feedback to generate obstacle-aware trajectories, a pivotal advance for stable, responsive manipulation under uncertainty. Daniel E. Koditschek [2] at University of Pennsylvania [4] and Yale University [5] advanced exact robot navigation using artificial potential functions [7], providing a rigorous framework that underpinned perception-driven planning. Daniel E. Koditschek [2] and colleagues further anchored this approach in the era by highlighting how artificial potential function-based navigation [7] supports robust control and impedance-like interaction for real-time manipulation under uncertainty.

Modular Distributed Coordination era

Hod Lipson [1], a leading researcher at Massachusetts Institute of Technology [3] and Cornell University [4] in this era, advanced modular self-reconfigurable robotics. His key contribution is the Modular Self-Reconfigurable Robot Systems [Grand Challenges of Robotics] [7] (2007), which demonstrated how modular, morphologically flexible robots enable scalable manipulation and collaborative behavior. Gregory S. Chirikjian [2], affiliated with Johns Hopkins University [5] and Washington University in St. Louis [6] during this era, contributed to the Modular Self-Reconfigurable Robot Systems [7] work by providing theoretical frameworks for modular kinematics and coordination. This Modular Self-Reconfigurable Robot Systems framework [7] helped establish distributed control, task-priority coordination, and cooperative manipulation across modular robots, underpinning load sharing and scalable planning in decentralized deployments.

Human-in-the-Loop Autonomy era

Lars Grimstad [1] is associated with institutions such as the Norwegian University of Life Sciences [3] and the University of Lincoln [4] in the Human-in-the-Loop Autonomy era. His work includes the autonomous strawberry-harvesting robot: Design, development, integration, and field evaluation [7] and the related strawberry harvesting robot with a cable-driven gripper [8], which collectively advance field-deployable automation and human–robot collaboration by enabling robust harvesting in dynamic environments. Siddhartha S Srinivasa [2] is affiliated with the University of Washington [5] and Carnegie Mellon University [6] in this era. His contributions include the policy-blending formalism for shared control [9] and CHIMP, the CMU Highly Intelligent Mobile Platform [10], which collectively shaped shared autonomy frameworks and intelligent mobile platforms in human-in-the-loop robotics.