12 accepted papers
Enabling robots to walk on yielding terrain is vital for applications ranging from disaster response to planetary exploration. While bipedal robots hold immense potential, their locomotion on deformable surfaces remains limited as current simulators fail to capture the spatiotemporal heterogeneity o
Enabling robots to walk on yielding terrain is vital for applications ranging from disaster response to planetary exploration. While bipedal robots hold immense potential, their locomotion on deformable surfaces remains limited as current simulators fail to capture the spatiotemporal heterogeneity o…
This letter addresses the inherent inefficiencies and limited agility of traditional gait-based locomotion by proposing the continuum drive paradigm as a high-performance alternative. Existing control frameworks are limited by their simplified predictive models and decoupled planners, which prevent
Recent advancements in legged robot locomotion and reinforcement learning have demonstrated significant potential for the development of bipedal robot. But the state estimation accuracy and bipedal robot locomotion robustness of Reinforcement Learning based (RL-based) controller is significantly inf
The hybrid aerial-ground robots combine ground mobility and aerial flight capability, which are often designed for executing multi-terrain tasks. However, most of the existing hybrid aerial-ground robots integrate the ground and aerial functionality into one single whole system. This leads to functi
Feasible regions for continuous walking must provide necessary information for footstep planning, including surrounding landing areas and details about obstacles to be avoided during foot swing. However, the current frame lacks sufficient information to construct a feasible region needed at the curr…
High-frequency and accurate state estimation is crucial for biped robots. This paper presents a tightly-coupled LiDAR-Inertial-Kinematic Odometry (LIKO) for biped robot state estimation based on an iterated extended Kalman filter. Beyond state estimation, the foot contact position is also modeled an…
Recent advances in both legged robot locomotion and Reinforcement Learning have shown a promising path for developing bipedal robot controllers. While the difference in dynamics between real world and simulation, also known as reality gap, still hinders the use. In this paper, we focus on sim-to-rea…
LiDAR-based semantic perception tasks are critical yet challenging for autonomous driving. Due to the motion of objects and static/dynamic occlusion, temporal information plays an essential role in reinforcing perception by enhancing and completing single-frame knowledge. Previous approaches either…
Compliance is important for humanoid robots, especially a position-controlled one, to perform tasks in complicated environments where unexpected or sudden contacts will result in large impacts which may cause instability or destroy the hardware of robots. This paper presents a compliance control met…
Generally, large knee joint torque is required when a leg is flexed. However, the large torque motor will increase the robot size and total weight. Also, a large reduction ratio gear box to realize the large torque will decrease output speed and lower backdrivability of the joint. It makes the robot…
Cats have protractible claws to fold their tips to keep them sharp. They protract claws while hunting and pawing on slippery surfaces. Protracted claws by tendons and muscles of toes can help cats anchoring themselves steady while their locomotion trends to slip and releasing the hold while they ret…