9 accepted papers
This letter presents a GPU-enabled parallel trajectory optimization framework for model predictive control (MPC) in complex urban environments. It fuses the advantages of sampling-based MPC, which can cope with nonconvex costmaps through random sampling of trajectories, with the advantages of gradie
This letter proposes a follower-stabilizing strategy for leader-waypoint-follower nonholonomic vehicle formation control. The follower-stabilizing strategy consists of the follower-stabilizing area and the follower's velocity correction term. When the follower crosses the waypoint generated by the l
Recently, several 4D radar datasets have been published due to its high resolution and robustness in extreme weather conditions. However, most of the recent 4D radar dataset publications have insufficient odometry sensors, which is disadvantageous for 4D radar odometry research. To tackle this probl
Nonlinear model predictive control (NMPC) is an efficient and proven method for optimization-based autonomous vehicle motion planning. Among the various approaches, the iterative linear quadratic regulator, a differential dynamic programming variant, is a well-known efficient nonlinear optimization
We present a transcutaneous electrical nerve stimulation (TENS) based sensory feedback strategy to simultaneously transmit two senses through a single channel for giving force and position information of the gripper to the user. The two sensations were delivered by mixing two differently shaped curr
Collision avoidance in emergency situations is a crucial and challenging task in motion planning for autonomous vehicles. Especially in the field of optimization-based planning using nonlinear model predictive control, many efforts to achieve real-time performance are still ongoing. Among various ap…
Amputees suffer from the weight, insufficient power, and uncomfortable control methods of their prostheses. Recent studies have introduced many ideas for both hardware and software to tackle these problems. In this letter, the authors introduce a preliminary platform of a robotic prosthetic hand sys
Input-output transmission ratio shifting mechanisms provide a variable transmission ratio, which effectively expands a speed-force operating range of actuators. Although it is the most effective solution to increase the performance of robotic systems, its application to compact robotic systems still…
Owing to the recent advances in the field of deep-learning-based approaches, state-of-the-art performance has been achieved for optical flow estimation. However, non-deep-learning-based improvement in the optical flow estimation performance is still required because many platforms, such as small UGV