Optical tweezers (OT) can be viewed as a robot that uses a highly focused laser beam for precise manipulation of biological objects and dielectric beads at micro-scale. Using holographic optical tweezers (HOT) multiple optical traps can be created to allow several operations in parallel. Moreover, due to the non-contact nature of manipulation OT can be potentially integrated with other manipulation techniques (e.g. microfluidics, acoustics, magnetics etc.) to ensure its high throughput. However, biological manipulation using OT suffers from two serious drawbacks: (1) slow manipulation due to manual operation and (2) severe effects on cell viability due to direct exposure of laser. This dissertation explores the problem of autonomous OT based cell manipulation in the light of addressing the two aforementioned limitations. Microfluidic devices are well suited for the study of biological objects because of their high throughput. Integrating microfluidics with OT provides precise position control as well as high throughput. An automated, physics-aware, planning approach is developed for fast transport of cells in OT assisted microfluidic chambers. The heuristic based planner employs a specific cost

function for searching over a novel state-action space representation. The effectiveness

of the planning algorithm is demonstrated using both simulation and physical

experiments in microfluidic-optical tweezers hybrid manipulation setup. An indirect

manipulation approach is developed for preventing cells from high intensity laser.

Optically trapped inert microspheres are used for manipulating cells indirectly either

by gripping or pushing. A novel planning and control approach is devised to

automate the indirect manipulation of cells. The planning algorithm takes the motion

constraints of the gripper or pushing formation into account to minimize the

manipulation time. Two different types of cells (Saccharomyces cerevisiae and

Dictyostelium discoideum) are manipulated to demonstrate the effectiveness of the

indirect manipulation approach.