The joint classification of hyperspectral image (HSI) and light detection and ranging (LiDAR) data is gaining attention for its improved classification accuracy. However, effectively integrating the rich spectral information of HSI and the elevation features of LiDAR has remained a challenge in multimodal fusion. This article proposes a novel approach called progressive semantic enhancement network

The physical body and its interaction with the environment shape robot behavior, simplify control, and minimize computation.

Coordinating the motion between lower and upper limbs and aligning limb control with perception are substantial challenges in robotics, particularly in dynamic environments. To this end, we introduce an approach for enabling legged mobile manipulators to play badminton, a task that requires precise coordination of perception, locomotion, and arm swinging. We propose a unified reinforcement learning–based

Achieving lifelike autonomy remains a long-term aspiration, yet soft robots so far have mostly demonstrated rudimentary physical intelligence that relies on manipulation of external stimuli to generate continuous motion. To realize autonomous physical intelligence (API) capable of self-regulated sensing, decision-making, and actuation, a promising approach is creating nonlinear time-lag feedback embedded

High-speed legged navigation in discrete and geometrically complex environments is a challenging task because of the high–degree-of-freedom dynamics and long-horizon, nonconvex nature of the optimization problem. In this work, we propose a hierarchical navigation pipeline for legged robots that can traverse such environments at high speed. The proposed pipeline consists of a planner and tracker module