• Real-time obstacle avoidance and autonomous navigation emerged as core field robotics capabilities, integrating sensor data, fast local planning, and in-motion mapping to handle dynamic environments [6], [12], [13], [20].

• Kinematics-driven motion planning unified design and control across mobile and legged platforms, linking kinematic modeling to trajectory generation and planning algorithms [2], [4], [8], [9].

• Legged and bio-inspired locomotion research pursued dynamic stability, energy-efficient gait design, and potential energy conserving strategies to enable field locomotion [1], [11], [16], [19].

• Autonomous road navigation and guidance expanded from rovers and road-following to autonomous-vehicle concepts for field environments, blending navigation, control, and perception [3], [5], [7], [18].

• Manipulation and grasping in field robotics emphasized coordinated manipulation, robotic grasping, and interaction with autonomous systems, integrating perception with manipulation [14], [17].