This paper studies the problem of obstacle avoidance and trajectory tracking for a class of uncertain nonlinear systems with unmeasured states and actuator faults. The main difficulty is that actuator faults may cause significant transient tracking errors, which might lead to collisions. To overcome this difficulty, an adaptive observer is developed to estimate system states and compensate for actuator faults. Additionally, the integral-multiplicative Barrier Lyapunov function (BLF) is integrated into the backstepping procedure to overcome the dynamics mismatching problem of the existing SUM-type BLF. The proposed adaptive scheme can avoid collisions in a multi-obstacle environment even if the actuator faults occur, and all the signals are uniformly ultimately bounded. Simulation results demonstrate the effectiveness of this approach.