A low-power motion estimation chip is designed for a wireless panoramic endoscope system. This chip consists of two motion estimation cores and is implemented by a dual-Vdd low-power technique. The proposed technique is efficient in decreasing power consumption without reducing the operation frequency of the chip. From the full-function chip measurements, this dual-Vdd chip can reduce power consumption by 20%~40% than the operation in single-Vdd for different clock frequencies.

A low-power motion estimation chip is designed for a wireless panoramic endoscope system. This chip consists of two motion estimation cores and is implemented by a dual-Vdd low-power technique. The proposed technique is efficient in decreasing power consumption without reducing the operation frequency of the chip. From the full-function chip measurements, this dual-Vdd chip can reduce power consumption by 20%∼40% than the operation in single-Vdd at different clock frequencies.

Light Detection and Ranging (LiDAR) is a high-price system for wide-usage automotive driving requirements. The design, implementation, and validation of a performance-complexity efficient LiDAR system are introduced in this paper. A Time-to-Digit (TDC) chip with a low-cost Data-Processing (DP) chip is utilized in this system. The proposed chips have been well validated and can be utilized as processing cores for a generic LiDAR system. The measurement accuracy is a comparison with a high-price commercial product of Time-Correlated Single-Photon-Counting (TCSPC). The values show the proposed system accuracy is respectable for the comparison by many distances from 4.8m to 44.6m, the maximum difference is 0.3%.

It is generally accepted that robotic surgery has increased in popularity which has revolutionized the medical field over the past few decades. Despite many successes and development, there are still a lot of challenges what was remained in the surgeries such as the requirement of haptic feedback system has become a raising issue due to a lot of failure cases during robotic surgery processes, for example: suture breakage because of pulling action in knot-tying, slipped on a needle of grasping action or inadequate of force. In this paper, an image-based force sensing feedback system is presented. The force feedback system can provide unmistakable for the surgeon how much force they are utilizing by showing corresponding colors, which can reduce instances of surgery failure without negatively impacting the surgeon 's performance. Visual images-based were employed to watching the distance changing of plasticity sensor during the time it was suffering an opposite reaction force from grasping action of a surgery robot arm. From the experiments, this visual images-based evaluation method can detect a minimum force value of 0.01 Newton. This system provides extraordinary accuracy of force sensing feedback and also hands controlling for a robot arm, due to the accuracy shows up to 99.96% (hands action recognition). The main distribution of this studying is to give robot-arm can use the proposed technique to estimate and utilize force values for surgical operation.