5 accepted papers
The control of pneumatic soft robotics is challenging due to nonlinearites arising from many factors including pneumatic system components and material properties of the soft actuator. Manual methods for PID controller tuning are inadequate for the nonlinear and time-variant dynamics present in soft…
The control of pneumatic soft robotics is challenging due to nonlinearites arising from many factors including pneumatic system components and material properties of the soft actuator. Manual methods for PID controller tuning are inadequate for the nonlinear and time-variant dynamics present in soft
Going beyond the traditional sparse multi-channel peripheral human-machine interface that has been used widely in neurorobotics, high-density surface electromyography (HD-sEMG) has shown significant potential for decoding upper-limb motor control. We have recently proposed heterogeneous temporal dil…
Deep networks have been recently proposed to estimate motor intention using conventional bipolar surface electromyography (sEMG) signals for myoelectric control of neurorobots. In this regard, Deepnets are generally challenged by long training times (affecting practicality and calibration), complex
Offroad mobile robot perception systems must be able to learn robust terrain classification models. Models built from computer vision often fail in their ability to generalize to new environments where appearance characteristics change. Sound and vibration signals from robot-terrain interaction can…